Research & ADS Tracks

Accepted Papers in Research Track

“Let’s Eat Grandma”: Does Punctuation Matter in Sentence Representation
Mansooreh Karami (Arizona State University)*; Ahmadreza Mosallanezhad (Arizona State University); Michelle Mancenido (Arizona State University); Huan Liu (Arizona State University)
A Class-Mixed Data Generation Approach to Out-Of-Distribution Detection
Mengyu Wang (Peking University)*; Yijia Shao (Peking University); Haowei Lin (Peking University); Wenpeng Hu (Peking University); Bing Liu (UIC)
A Heterogeneous Propagation Graph Model for Rumor Detection under the Relationship among Multiple Propagation Subtrees
Li Guoyi (Institute of Information Engineering, Chinese Academy of Sciences)*; Jingyuan Hu (Institute of Information Engineering, Chinese Academy of Sciences); Yulei Wu (University Of Exeter); Zhang Xiaodan (Institute of Information Engineering, Chinese Academy of Sciences); Wei Zhou (Institute of Information Engineering, School of Cyber Security, University of Chinese Academy of Sciences); Lyu Honglei (Institute of Information Engineering, Chinese Academy of Sciences)
A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded Corruptions
Ramya S Hebbalaguppe (Indian Institute of Technology, Delhi)*; Soumya Suvra Ghosal (University of Wisconsin-Madison); Jatin Prakash (Indian Institute of Technology, Delhi); Harshad Khadilkar (IIT Mumbai); Chetan Arora (Indian Institute of Technology Delhi)
Vijay Lingam (Microsoft Research India)*; Manan Sharma (Microsoft Research); Chanakya Ekbote (Microsoft); Rahul Ragesh (Microsoft); Arun Iyer (Microsoft Research); Sundararajan Sellamanickam (Microsoft Research)
A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective
Hiroaki Mikami (Preferred Networks, Inc.); Kenji Fukumizu (The Institute of Statistical Mathematics); Shogo Murai (Preferred Networks, Inc.); Shuji Suzuki (Preferred Networks, Inc.); Yuta Kikuchi (Preferred Networks, Inc.); Taiji Suzuki (The University of Tokyo / RIKEN); Shin-ichi Maeda (Preferred Networks, inc.); Kohei Hayashi (Preferred Networks, Inc.)*
A Stopping Criterion for Transductive Active Learning
Daniel Kottke (University of Kassel)*; Christoph Sandrock (University of Kassel); Georg Krempl (Utrecht University); Bernhard Sick (University of Kassel)
A U-shaped Hierarchical Recommender for Multi-resolution Collaborative Signal Modeling
Peng YI (UNSW); Xiongcai Cai (UNSW Sydney)*; Ziteng Li (UNSW Sydney )
AD-AUG: Adversarial Data Augmentation for Counterfactual Recommendation
Yifan Wang (Peking University)*; Yifang Qin (Peking University); Yu Han (Alibaba Group); Mingyang Yin (Alibaba Group); Jingren Zhou (Alibaba Group); Hongxia Yang (Alibaba Group); Ming Zhang (Peking University)
Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition Models
Alon Zolfi (Ben-Gurion University of the Negev)*; Shai Avidan (TAU Eng.); Yuval Elovici (Ben-Gurion University of the Negev); Asaf Shabtai (Ben-Gurion University of the Negev)
Adversarial Projections to Tackle Support-Query Shifts in Few-Shot Meta-Learning.
Aroof Aimen (Indian Institute of Techology, Ropar)*; Bharat Ladrecha (Indian Institute of Technology Ropar); Narayanan C Krishnan (IIT Palakkad)
Adversarially Robust Decision Tree Relabeling
Daniël Vos (Delft University of Technology)*; Sicco Verwer (Delft University of Technology)
Algorithmic Tools for Mining the Motif Structure of Networks
Tianyi Chen (Boston University); Brian Matejek (Harvard University ); Michael Mitzenmacher (Harvard); Charalampos Tsourakakis (Boston University)*
An Ion Exchange Mechanism Inspired Story Ending Generator for Different Characters
Xinyu Jiang (Beijing Institute of Technology); Qi Zhang (University of Technology Sydney); Chongyang Shi (Beijing Institute of Technology)*; Kaiying Jiang (University of Science and Technology Beijing); Liang Hu (Tongji University); Shoujin Wang (Macquarie University)
Anomaly Detection via Few-shot Learning on Normality
Shin Ando (Tokyo University of Science)*; Ayaka Yamamoto (Tokyo University of Science)
Anonymity Can Help Minority: A Novel Synthetic Data Over-sampling Strategy on Multi-label Graphs
YIJUN DUAN (NAIST)*; Xin Liu (National Institute of Advanced Industrial Science and Technology (AIST)); Adam Jatowt (Kyoto University); Hai-Tao Yu (University of Tsukuba); Steven Lynden (National Institute of Advanced Industrial Science and Technology (AIST)); Kyoung-Sook Kim (Artificial Intelligence Research Center); Akiyoshi Matono (AIST)
ARES: Locally Adaptive Reconstruction-based Anomaly Scoring
Adam Goodge (National University of Singapore)*; Bryan Hooi (NUS); See Kiong Ng (National University of Singapore); Wee Siong Ng (Institute for Infocomm Research, Singapore)
Attention, Filling in The Gaps for Generalization in Routing Problems
Ahmad Bdeir (University of Hildesheim)*; Jonas K Falkner (University of Hildesheim); Lars Schmidt-Thieme (Universität Hildesheim)
AutoMap: Automatic Medical Code Mapping for Clinical Prediction Model Deployment
Zhenbang Wu (UIUC)*; Cao Xiao (Amplitude); Lucas M Glass (Temple University); David M Liebovitz (Northwestern University); Jimeng Sun (UIUC)
Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks
Ghada Sokar (Eindhoven University of Technology (TU/e))*; Decebal Constantin Mocanu (University of Twente); Mykola Pechenizkiy (TU Eindhoven)
Basket Booster for Prototype-based Contrastive Learning in Next Basket Recommendation
Su Ting-Ting (Sun Yat-Sen University); Zhen-Yu He (Sun Yat-sen University); Man-Sheng Chen (Sun Yat-sen University); Chang-Dong Wang (Sun Yat-sen University)*
Batch Reinforcement Learning from Crowds
Guoxi Zhang (Kyoto University)*; Hisashi Kashima (Kyoto University)
Bayesian Nonparametrics for Sparse Dynamic Networks
Cian V Naik (University of Oxford)*; Francois Caron (Oxford); Judith Rousseau (University of Oxford); Yee Whye Teh (University of Oxford); Konstantina Palla (Microsoft Research UK)
Beyond Random Selection: A Perspective from Model Inversion in Personalized Federated Learning
Zichen Ma (The Chinese University of Hong Kong, Shenzhen)*; Yu Lu (The Chinese University of Hong Kong, Shenzhen); Wenye Li (The Chinese University of Hong Kong, Shenzhen); Shuguang Cui (The Chinese University of Hong Kong, Shenzhen)
Bi-directional Contrastive Distillation for Multi-behavior Recommendation
Yabo Chu (Northeastern University)*; Enneng Yang (Northeastern University); Qiang Liu (Institute of Automation, Chinese Academy of Sciences); Yuting Liu (Northeastern University); Linying Jiang (Software College, Northeastern University); Guibing Guo (Northeastern University)
Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning
Md Masudur Rahman (Purdue University)*; Yexiang Xue (Purdue University)
Bounding the Family-Wise Error Rate in Local Causal Discovery using Rademacher Averages
Dario Simionato (University of Padua); Fabio Vandin (University of Padova)*
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
Zeren Huang (Shanghai Jiao Tong University)*; Wenhao Chen (SJTU); Weinan Zhang (Shanghai Jiao Tong University); Chuhan Shi (Shanghai Jiao Tong University); Furui Liu (Huawei Noah’s Ark Lab); Hui-Ling Zoe Zhen (Huawei); Mingxuan Yuan (Huawei); Jianye Hao (Tianjin University); Yong Yu (Shanghai Jiao Tong University); Jun Wang (UCL)
Calibrate to interpret
Gregory D Scafarto (EURA NOVA)*; Antoine Bonnefoy (EURA NOVA); Nicolas P Posocco (EURA NOVA)
Calibrating Distance Metrics Under Uncertainty
Wenye Li (The Chinese University of Hong Kong, Shenzhen)*; Fangchen Yu (The Chinese University of Hong Kong, Shenzhen)
CDPS: Constrained DTW-Preserving Shapelets
Hussein EL AMOURI (University of Strasbourg)*; Thomas Lampert (University of Strasbourg); Pierre Gançarski (University of Strasbourg); Clement Mallet (“IGN, France”)
Charge Own Job: Saliency Map and Visual Word Encoder for Image-Level Semantic Segmentation
Yuhui Guo (Renmin University of China)*; Xun Liang (Renmin University of China); hui tang (Renmin University of China); Xiangping Zheng (Renmin University of China); Bo Wu (Renmin University of China); Xuan Zhang (Renmin University of China)
Class-Incremental Learning via Knowledge Amalgamation
Marcus de Carvalho (Nanyang Technological University)*; Mahardhika Pratama (University of South Australia); Jie Zhang (Nanyang Technological University); YAJUAN SUN (A*Star SIMTech)
Consistent and Tractable Algorithm for Markov Network learning
Vojtech Franc (Center for Machine Perception)*; Daniel Prusa (Czech Technical University in Prague); Andrii Yermakov (Czech Technical University in Prague)
Constrained Multiagent Reinforcement Learning for Large Agent Population
Jiajing LING (Singapore Management University)*; Arambam James Singh (National University of Singapore); Duc Thien Nguyen (Singapore Management University); Akshat Kumar (Singapore Management University)
Context Abstraction to Improve Decentralized Machine Learning in Structured Sensing Environments
Massinissa Hamidi (Laboratoire LIPN-UMR CNRS 7030, PRES Sorbonne Paris Cité)*; Aomar Osmani (Laboratoire LIPN-UMR CNRS 7030, PRES Sorbonne Paris Cité)
Contextual Information and Commonsense Based Prompt for Emotion Recognition in Conversation
Yi Jingjie (Fudan University); Deqing Yang (Fudan University)*; Siyu Yuan (Fudan University); Cao Kaiyan (School of Data Science in Fudan University); zhang zhiyao (fudan university); Yanghua Xiao (Fudan University)
Customized Conversational Recommender Systems
Shuokai Li (Institute of Computing Technology, Chinese Academy of Sciences)*; Yongchun Zhu (Institute of Computing Technology, Chinese Academy of Sciences); Ruobing Xie (WeChat Search Application Department, Tencent); Zhenwei Tang (King Abdullah University of Science and Technology); Zhao Zhang (Institute of Computing Technology, Chinese Academy of Sciences ); Fuzhen Zhuang (Institute of Artificial Intelligence, Beihang University); Qing He (Institute of Computing Technology, Chinese Academy of Sciences); Hui Xiong (the State University of New Jersey)
Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising
Zikang Xiong (Purdue University )*; Joe K Eappen (Purdue University); He Zhu (Rutgers University); Suresh Jagannathan (Purdue University)
DeMis: Data-efficient Misinformation Detection using Reinforcement Learning
Kornraphop Kawintiranon (Georgetown University)*; Lisa Singh (Georgetown University)
Detecting Anomalies with Autoencoders on Data Streams
Lucas Cazzonelli (FZI Research Center for Information Technology)*; Cedric Kulbach (FZI Research Center for Information Technology)
DialCSP: A Two-stage Attention-based Model for Customer Satisfaction Prediction in E-commerce Customer Service
Zhenhe Wu (beihang university)*; Liangqing Wu (JD AI Research); Shuangyong Song (Jing Dong); Jiahao Ji (Beihang University); Bo Zou (JD AI Research); Zhoujun Li (Beihang University); Xiaodong He (Jing Dong)
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability
Qiyiwen Zhang (University of Pennsylvania – Philadelphia, PA)*; Zhiqi Bu (University of Pennsylvania); Kan Chen (University of Pennsylvania); Qi Long (University of Pennsylvania)
Differentially Private Federated Combinatorial Bandits with Constraints
Sambhav Solanki (Machine Learning Lab, International Institute of Information Technology Hyderabad )*; Samhita Kanaparthy (Machine Learning Lab, International Institute of Information Technology Hyderabad); Sankarshan Damle (Machine Learning Lab, International Institute of Information Technology, Hyderabad); Sujit Gujar (Machine Learning Laboratory, International Institute of Information Technology, Hyderabad)
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents
Jakob Drefs (Carl von Ossietzky Universität Oldenburg)*; Enrico Guiraud (CERN); Filippos S Panagiotou (Carl von Ossietzky University Oldenburg); Jörg Lücke (Universität Oldenburg)
Discovering wiring patterns influencing neural network performance
Aleksandra I Nowak (Jagiellonian Univeristy)*; Romuald Janik (Jagiellonian University)
Distributional Correlation–Aware Knowledge Distillation for Stock Trading Volume Prediction
Lei Li (Peking University)*; Zhiyuan Zhang (Peking University); Ruihan Bao (Mizuho Bank); Keiko Harimoto (Mizuho Bank); Xu Sun (Peking University)
DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems
Joe K Eappen (Purdue University)*; Suresh Jagannathan (Purdue University)
Do You Know My Emotion? Emotion-Aware Strategy Recognition towards a Persuasive Dialogue System
Wei Peng (Institute of Information Engineering, Chinese Academy of Sciences)*; Yue Hu (Institute of Information Engineering,Chinese Academy of Sciences); Luxi Xing (Institute of Information Engineering, Chinese Academy of Sciences); Yuqiang Xie (Institute of Information Engineering, Chinese Academy of Sciences); Yajing Sun (Institute of Information Engineering,Chinese Academy of Sciences)
Edge but not Least: Cross-View Graph Pooling
Xiaowei Zhou (University of Technology Sydney)*; Jie Yin (The University of Sydney); Ivor Tsang (University of Technology Sydney)
Efficient Automated Deep Learning for Time Series Forecasting
Difan Deng ( Leibniz Universität Hannover)*; Florian M Karl (Fraunhofer-Institut für Integrierte Schaltungen IIS); Frank Hutter (University of Freiburg); Bernd Bischl (LMU Munich); Marius Lindauer (Leibniz University Hannover)
Enhance Temporal Knowledge Graph Completion via Time-aware Attention Graph Convolutional Network
Haohui Wei (Huazhong University of Science and Technology); Hong Huang (Huazhong University of Science and Technology)*; Teng Zhang (Huazhong University of Science and Technology); Xuanhua Shi (Huazhong University of Science and Technology); Hai Jin (Huazhong University of Science and Technology)
EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting
Feng Xie (National University of Defense Technology)*; Zhong Zhang (National University of Defense Technology); Liang Li (National University of Defense Technology); Bin Zhou (National University of Defense Technology); yusong tan (College of Computer, National University of Defense Technology)
Explaining Predictions by Characteristic Rules
Amr Alkhatib (KTH Royal Institute of Technology)*; Henrik Bostrom (KTH Royal Institute of Technology); Michalis Vazirgiannis (KTH Royal Institute of Technology)
Exploring Latent Sparse Graph for Large-Scale Semi-supervised Learning
Zitong Wang (Columbia University in the City of New York); Li Wang (University of Texas at Arlington)*; Raymond Chan (City University of Hong Kong); Tieyong Zeng (The Chinese University of Hong Kong)
Fair and Efficient Alternatives to Shapley-based Attribution
Charles Condevaux (Université de Nîmes)*; Sébastien HARISPE (IMT Mines Alès); Stéphane Pr. Mussard (CHROME)
FairDistillation: Mitigating Stereotyping in Language Models
Pieter Delobelle (KU Leuven)*; Bettina Berendt (KU Leuven)
FASE: A Fast, Accurate and Seamless Emulator for Custom Numerical Formats
John H Osorio Ríos (Barcelona Supercomputing Center)*; Adrià Armejach (Barcelona Supercomputing Center); Eric Petit (Intel); Greg Henry (Intel); Marc Casas Guix (Barcelona Supercomputing Center)
Fast and Accurate Importance Weighting for Correcting Sample Bias
Antoine de Mathelin (ENS Paris-Saclay)*; François Deheeger (Michelin); Mathilde J MOUGEOT (ENS Paris Saclay); Nicolas Vayatis (ENS Paris Saclay)
FastDEC: Clustering By Fast Dominance Estimation
Geping Yang (Guangdong Universty of Technology); Hongzhang Lv (Guangdong University of Technology); Yiyang Yang (Guangdong Universty of Technology)*; Zhiguo Gong (University of Macau); Xiang Chen (Sun Yat-sen University); Zhifeng Hao (Shantou University)
Feature-Robust Optimal Transport for High-Dimensional Data
Mathis Petrovich (ENS-PARIS-SACLAY); Chao Liang (Zhejiang University); Ryoma Sato (Kyoto University); Yanbin Liu (The University of Western Australia); Yao-Hung Tsai (Carnegie Mellon University); Linchao Zhu (University of Technology, Sydney); Yi Yang (UTS); Ruslan Salakhutdinov (Carnegie Mellon University); Makoto Yamada (RIKEN AIP / Kyoto University)*
Few-Shot Forecasting of Time-Series with Heterogeneous Channels
Lukas Brinkmeyer (Universität Hildesheim); Rafael Rego Drumond (Universität Hildesheim)*; Johannes Burchert (Universität Hildesheim); Lars Schmidt-Thieme (University of Hildesheim)
Finding Local Groupings of Time Series
Zed Lee (Stockholm University)*; Marco Trincavelli (H&M Group); Panagiotis Papapetrou (Stockholm University)
Fine-Grained Matching with Iterative Knowledge Dissemination for Cross-Modal Retrieval
Xiumin Xie (Guangxi Normal University); Chuanwen Hou (Guangxi Normal University); Zhixin Li (Guangxi Normal University)*
Fooling Partial Dependence via Data Poisoning
Hubert Baniecki (Warsaw University of Technology)*; Wojciech Marek Kretowicz (Warsaw University of Technology); Przemyslaw Biecek (Warsaw University of Technology)
Foveated Neural Computation
Matteo Tiezzi (University of Siena)*; Simone Marullo (University of Siena); Alessandro Betti (Université Côte d’Azur); Enrico Meloni (University of Florence, University of Siena); Lapo Faggi (University of Florence, University of Siena); Marco Gori (University of Siena); Stefano Melacci (University of Siena)
FROB: Few-shot ROBust Model for Joint Classification and Out-of-Distribution Detection
Nikolaos Dionelis (The University of Edinburgh)*; Sotirios Tsaftaris (The University of Edinburgh); Mehrdad Yaghoobi (The University of Edinburgh)
From graphs to DAGs: a low-complexity model and a scalable algorithm
Shuyu Dong (LISN – INRIA, Université Paris-Saclay)*; Michele Sebag (CNRS, Université Paris-Saclay)
GNN Transformation Framework for Improving Efficiency and Scalability
Seiji Maekawa (Osaka University)*; Yuya Sasaki (Osaka University); George Fletcher (Eindhoven University of Technology); Makoto Onizuka (Osaka University)
GNNSampler: Bridging the Gap between Sampling Algorithms of GNN and Hardware
Xin Liu (Institute of Computing Technology Chinese Academy of Sciences)*; Mingyu Yan (Institute of Computing Technology Chinese Academy of Sciences); shuhan song (University of Chinese Academy of Sciences); zhengyang Lv (Institute of Computing Technology Chinese Academy of Sciences); wenming Li (Institute of Computing Technology Chinese Academy of Sciences); Guangyu Sun (Peking University); Xiaochun Ye (Institute of Computing Technology Chinese Academy of Sciences); Dongrui Fan (ICT, Chinese Academy of Sciences)
Graph Contrastive Learning with Adaptive Augmentation for Recommendation
Mengyuan Jing (Shanghai Jiao Tong University)*; Yanmin Zhu (Shanghai Jiao Tong University); Tianzi Zang (Shanghai Jiao Tong University); Jiadi Yu (Shanghai Jiao Tong University); Feilong Tang (Shanghai Jiao Tong University)
GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction
Lirong Wu (Westlake University)*; Jun Xia (Westlake University and Zhejiang University); Zhangyang Gao (westlake university); Haitao Lin (westlake university); Cheng Tan (Westlake University); Stan Z. Li (Westlake University)
Heterogeneity Breaks the Game: Evaluating Cooperation-Competition with Multisets of Agents
Yue Zhao (Northwestern Polytechnical University)*; José Hernández-Orallo (Universitat Politècnica de València)
Hierarchical Unimodal Bandits
TIANCHI ZHAO (The University of Arizona)*; Chicheng Zhang (University of Arizona); Ming Li (University of Arizona)
Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks
Tianjin Huang (Eindhoven University of Technology)*; Yulong Pei (TU Eindhoven); Vlado Menkovski (Eindhoven University of Technology); Mykola Pechenizkiy (TU Eindhoven)
Hyperbolic Deep Keyphrase Generation
yuxiang zhang (Civil Aviation University of China)*; Tianyu Yang (Civil Aviation University of China); Tao Jiang (Civil Aviation University of China); Xiaoli Li (Institute for Infocomm Research , A*STAR, Singapore/Nanyang Technological University); Suge Wang (Shanxi University)
Hypothesis Testing for Class-Conditional Label Noise
Rafael Poyiadzis (University of Bristol)*; Weisong Yang (University of Bristol); Niall Twomey (University of Bristol); Raul Santos Rodriguez (University of Bristol)
Hypothesis Transfer in Bandits by Weighted Models
Steven Bilaj (University of Tübingen)*; Sofien Dhouib (University of Tübingen); Setareh Maghsudi (University of Tübingen)
Image-Text Matching with Fine-Grained Bidirectional Attention-Based Generative Networks
Jianwei Zhu (Guangxi Normal University); Zhixin Li (Guangxi Normal University)*; Jiahui Wei (Guangxi Normal University); Yufei Zeng (Guangxi Normal University)
Imitation Learning with Sinkhorn Distances
Georgios Papagiannis (Imperial College London)*; Yunpeng Li (University of Surrey)
Immediate Split Trees: Immediate Encoding of Floating Point Split Values in Random Forests
Christian Hakert (TU Dortmund)*; Kuan-Hsun Chen (University of Twente); Jian-Jia Chen (TU Dortmund)
Improved Regret Bounds for Online Kernel Selection under Bandit Feedback
Junfan Li (Tianjin University); Shizhong Liao (Tianjin University)*
Improving Actor-Critic Reinforcement Learning via Hamiltonian Monte Carlo Method
Duo Xu (Georgia Institute of Technology)*
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Reinforcement Learning
Bogdan Mazoure (MILA,McGill University)*; Paul Mineiro (Microsoft); Pavithra Srinath (Microsoft Research); Reza Sharifi Sedeh (Microsoft); Doina Precup (McGill University); Adith Swaminathan (Microsoft Research)
InCo: Intermediate Prototype Contrast for Unsupervised Domain Adaptation
Yuntao Du (Nanjing University)*; Hongtao Luo (Nanjing University); Haiyang Yang (Nanjing University); juan jiang (Nanjing University); Chongjun Wang (Nanjing University)
Inferring Tie Strength in Temporal Networks
Lutz Oettershagen (University of Bonn)*; Athanasios Konstantinidis (Luiss University); Giuseppe F. Italiano (LUISS University)
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach
Ancy Tom (University of Minnesota, Twin Cities)*; Nesreen Ahmed (Intel Labs); George Karypis (University of Minnesota, Twin Cities)
Knowledge Integration in Deep Clustering
Nguyen-Viet-Dung Nghiem (University of Orléans)*; Thi-Bich-Hanh Dao (University of Orleans); Christel Vrain (University of Orleans)
Knowledge-Driven Interpretation of Convolutional Neural Networks
Riccardo Massidda (Università di Pisa)*; Davide Bacciu (Univeristy of Pisa)
LCDB 1.0: An extensive Learning Curves Database for Classification Tasks
Felix Mohr (Universidad de La Sabana)*; Tom J Viering (Delft University of Technology, Netherlands); Marco Loog (Delft University of Technology & University of Copenhagen); Jan Van Rijn (Leiden University)
Learnable Masked Tokens for Improved Transferability of Self-Supervised Vision Transformers
Hao Hu (KTH Royal Institute of Technology)*; Federico Baldassarre (KTH – Royal Institute of Technology); Hossein Azizpour (KTH (Royal Institute of Technology))
Learning Optimal Decision Trees Under Memory Constraints
Gael Aglin (UCLouvain)*; Siegfried Nijssen (Université Catholique de Louvain, BE); Pierre Schaus (UC Louvain)
Learning optimal transport between two empirical distributions with normalizing flows
Florentin Coeurdoux (University of Toulouse)*; Nicolas Dobigeon (University of Toulouse); Pierre Chainais (Centrale Lille / CRIStAL CNRS UMR 9189)
Learning Perceptual Position-aware Shapelets for Time series Classification
Xuan-May Le (JAIST)*; Minh-Tuan Tran (KAIST); Nam Huynh (Japan Advanced Institute of Science and Technology, Japan)
Learning to Control Local Search for Combinatorial Optimization
Jonas K Falkner (University of Hildesheim)*; Daniela Thyssens (University of Hildesheim); Ahmad Bdeir (University of Hildesheim); Lars Schmidt-Thieme (University of Hildesheim)
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
Steffen Jung (MPII)*; Margret Keuper (University of Mannheim)
Learning to Teach Fairness-aware Deep Multi-Task Learning
Arjun Roy (L3S Research Center)*; Eirini Ntoutsi (Freie Universität Berlin)
LSCALE: Latent Space Clustering-Based Active Learning for Node Classification
Juncheng Liu (National University of Singapore)*; Yiwei WANG (National University of Singapore); Bryan Hooi (National University of Singapore); Renchi Yang (National University of Singapore); Xiaokui Xiao (National University of Singapore)
Marginal Release under Multi-Party Personalized Differential Privacy
Peng Tang (Shandong University)*; Rui Chen (Harbin Engineering University); Chongshi Jin (Shangdong University); Gaoyuan Liu (Shandong University); Shanqing GUO (Shandong University)
Masked Graph Auto-Encoder Constrained Graph Pooling
Chuang Liu (Wuhan University)*; Yibing Zhan (JD Explore Academy); Xueqi Ma (Tsinghua University); Dapeng Tao (Yunnan University); Bo Du (Wuhan University); Wenbin Hu (Wuhan University)
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
Stephanie Milani (Carnegie Mellon University)*; Zhicheng Zhang (Shanghai Jiao Tong University); Nicholay Topin (Carnegie Mellon University); Zheyuan Ryan Shi (Carnegie Mellon University); Charles Kamhoua (Army Research Lab); Evangelos Papalexakis (UC Riverside); Fei Fang (Carnegie Mellon University)
MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors
Federica Granese (INRIA – LIX – Sapienza University of Rome)*; Marine Picot (CentraleSupélec – CNRS – L2S); Marco Romanelli (CentraleSupélec – CNRS – L2S); Francisco Messina (University of Buenos Aires); Pablo Piantanida ( CNRS Université Paris-Saclay )
MFDG: a Multi-Factor Dialogue Graph Model for Dialogue Intent Classification
Jinhui Pang (Beijing Institute of Technology); Huinan Xu (Beijing Institute Of Technology)*; Shuangyong Song (Jing Dong); Bo Zou (JD AI Research); Xiaodong He (JD AI Research)
Mitigating Confounding Bias for Recommendation via Counterfactual Inference
Ming He (Beijing University of Technology)*; Xinlei Hu (Beijing University Of Technology); Changshu Li (Beijing University Of Technology); Xin Chen (Beijing University Of Technology); Jiwen Wang ( Beijing University of Technology)
Mixed Integer Linear Programming for Optimizing a Hopfield Network
Bodo Rosenhahn (Leibniz University Hannover)*
Model Selection in Reinforcement Learning with General Function Approximations
Avishek Ghosh (University of California, San Diego)*; Sayak Ray Chowdhury (Indian Institute of Science)
MRF-UNets: Searching UNet with Markov Random Fields
Zifu Wang (KU Leuven)*; Matthew B. Blaschko (KU Leuven)
Multi-Agent Heterogeneous Stochastic Linear Bandits
Avishek Ghosh (University of California, San Diego)*; Abishek Sankararaman (Amazon); Ramchandran Kannan (Department of Electrical Engineering and Computer Science University of California, Berkeley)
Multi-domain Active Learning for Semi-supervised Anomaly Detection
Vincent Vercruyssen (KU Leuven)*; Lorenzo Perini (KU Leuven); Wannes Meert (KU Leuven); Jesse Davis (KU Leuven)
Multi-Interest Extraction Joint with Contrastive Learning for News Recommendation
ShiCheng Wang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China)*; Shu Guo (National Computer Network Emergency Response Technical Team & Coordination Center of China); lihong wang (CNCERT); Tingwen Liu (Institute of Information Engineering, CAS); Hongbo Xu (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China)
Multi-Objective Actor-Critics for Real-Time Bidding
Haolin Zhou (Shanghai Jiaotong University); Chaoqi Yang (University of Illinois at Urbana-Champaign); Xiaofeng Gao (Shanghai Jiaotong University)*; Qiong Chen (Tencent); Gongshen Liu (Shanghai Jiao Tong University); Guihai Chen (Shanghai Jiao Tong University)
Multi-source Inductive Knowledge Graph Transfer
Junheng Hao (UCLA)*; Lu-An Tang (NEC Labs America); Yizhou Sun (UCLA); Zhengzhang Chen (NEC Laboratories America, Inc.); Haifeng Chen (NEC Labs); Junghwan Rhee (University of Central Oklahoma); Zhichun Li (Stellar Cyber); Wei Wang (UCLA)
Multi-Task Adversarial Learning for Semi-Supervised Trajectory-User Linking
Sen Zhang (Nanjing University of Aeronautics and Astronautics); Senzhang Wang (Central South University)*; Shigeng Zhang (Central South University); Hao Miao (Aalborg University); Xiang Wang (National University of Defense Technology); Junxing Zhu (National University of Defense Technology)
NE-WNA: A novel network embedding framework without neighborhood aggregation
Jijie Zhang (Heilongjiang University); Yan Yang (Heilongjiang University); Yong Liu (Heilongjiang university)*; Meng Han (Zhejiang University)
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance
Shibal Ibrahim (Massachusetts Institute of Technology)*; Natalia Ponomareva (Google Research); Rahul Mazumder (Massachusetts Institute of Technology)
No More Strided Convolutions or Pooling: A Novel CNN Architecture for Low-Resolution Images and Small Objects
Raja Sunkara (Missouri University of Science & Technology); Tony Luo (Department of Computer Science, Missouri University of Science and Technology)*
Noise-efficient Learning of Differentially Private Partitioning Machine Ensembles
Zhanliang Huang (University of Birmingham)*; Yunwen Lei (University of Birmingham); Ata Kaban (University of Birmingham)
Non-IID Distributed Learning with Optimal Mixture Weights
Bojian Wei (Institute of Information Engineering, Chinese Academy of Sciences); Jian Li (Institute of Information Engineering, CAS)*; Yong Liu (Renmin University of China ); Weiping Wang (Institute of Information Engineering, CAS, China)
Non-Parameteric Bayesian Approach for Uplift Discretization and Feature Selection
Mina RAFLA (Orange Labs)*; nicolas Voisine (Orange); Bruno Cremilleux (Université de Caen Normandie); Marc Boulle (Orange Labs)
Nonparametric Bayesian Deep Visualization
Haruya Ishizuka (Bridgestone Corporation)*; Daichi Mochihashi (Institute of Statistical Mathematics)
On Projectivity in Markov Logic Networks
Sagar Malhotra (Fondazione Bruno Kessler)*; Luciano Serafini (Fondazione Bruno Kessler)
On the complexity of All $\epsilon$-Best Arms Identification
Aymen Al Marjani (ENS Lyon)*; Tomáš Kocák (University of Potsdam); Aurélien Garivier (ENS Lyon)
On the current state of reproducibility and reporting of uncertainty for Aspect-based Sentiment Analysis
Elisabeth Lebmeier (Ludwig-Maxmilians-Universität München); Matthias Aßenmacher (Ludwig-Maxmilians-Universität München)*; Christian Heumann (Ludwig-Maxmilians-Universität München)
On the Generalization of Neural Combinatorial Optimization Heuristics
Sahil Manchanda (IIT Delhi)*; Sofia Michel (Naverlabs Europe); Darko Drakulic (Naverlabs Europe); Jean-Marc Andreoli (Naverlabs Europe)
On the Prediction Instability of Graph Neural Networks
Max Klabunde (University of Passau)*; Florian Lemmerich (University of Passau)
On the relationship between disentanglement and multi-task learning
Łukasz Maziarka (Jagiellonian University)*; Aleksandra Nowak (Jagiellonian University); Maciej Wołczyk (Jagiellonian University); Andrzej Bedychaj (Jagiellonian University)
Online Adaptive Multivariate Time Series Forecasting
Amal Saadallah (TU Dortmund)*; Hanna Mykula (TU Dortmund); Katharina J. Morik (TU Dortmund)
Online learning of convex sets on graphs
Maximilian Thiessen (TU Wien)*; Thomas Gärtner (TU Wien)
Optimization of Annealed Importance Sampling Hyperparameters
Shirin Goshtasbpour (ETH Zurich)*; Fernando Perez-Cruz (ETH Zurich)
Oracle-SAGE: planning ahead in graph-based deep reinforcement learning
Andrew Chester (RMIT University)*; Michael Dann (RMIT University); Fabio Zambetta (RMIT University); John Thangarajah (RMIT University)
Ordinal Quantification through Regularization
Mirko Bunse (TU Dortmund University)*; Alejandro Moreo (ISTI-CNR); Fabrizio Sebastiani (Consiglio Nazionale delle Ricerche); Martin Senz (TU Dortmund University)
Overcoming Catastrophic Forgetting via Direction-Constrained Optimization
Yunfei Teng (New York University)*; Anna Choromanska (NYU); Murray Campbell (IBM Research); Songtao Lu (IBM Thomas J. Watson Research Center); Parikshit Ram (IBM Research AI); Lior Horesh (IBM Research)
Pass-Efficient Randomized SVD with Boosted Accuracy
Xu Feng (Tsinghua University)*; Wenjian Yu (Tsinghua University); Yuyang Xie (Tsinghua University)
Penalised FTRL With Time-Varying Constraints
Douglas Leith (Trinity College Dublin)*; George Iosifidis (TU Delft)
Physically Invertible System Identification for Monitoring System Edges with Unobservability
Jingyi Yuan (Arizona State University)*; Yang Weng (Arizona State University)
Powershap: A power-full shap feature selection method
Jarne Verhaeghe (imec – Ghent University, IDLab)*; Jeroen Van Der Donckt (UGent – imec); Femke Ongenae (imec – Ghent University, IDLab); Sofie Van Hoecke (UGent-imec )
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations
Tianle Zhang (University of Exeter); Wenjie Ruan (University of Exeter)*; Jonathan Fieldsend (University Of Exeter)
Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks
Jiaying Wu (National University of Singapore)*; Bryan Hooi (National University of Singapore)
ProcK: Machine Learning for Knowledge-Intensive Processes
Tobias Jacobs (NEC Laboratories Europe GmbH)*; Jingyi Yu (RWTH Aachen University); Julia Gastinger (NEC Laboratories Europe GmbH); Timo Sztyler (NEC Laboratories Europe GmbH)
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification
Dawid Damian Rymarczyk (Jagiellonian University)*; Aneta Kaczyńska (Jagiellonian University); Jarosław Kaus (Jagiellonian University); Adam Pardyl (Jagiellonian University); Marek Skomorowski (Jagiellonian University); Bartosz Zieliński (Jagiellonian University)
PrUE: Distilling knowledge from sparse teacher networks
Shaopu Wang (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China); Xiaojun CHEN (Institute of Information Engineering, CAS)*; Mengzhen Kou (Institute of Information Engineering, Chinese Academy of Sciences;School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China); Jinqiao Shi (Beijing University of Posts and Telecommunications)
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient
Jan-Philipp Schulze (Fraunhofer AISEC)*; Philip Sperl (Fraunhofer AISEC); Ana Radutoiu (Technische Universität München); Carla Christin Sagebiel (Fraunhofer AISEC); Konstantin Böttinger (Fraunhofer AISEC)
Random Similarity Forest
Maciej Piernik (Poznan University of Technology)*; Dariusz Brzezinski (Poznan University of Technology); Pawel Zawadzki (Adam Mickiewicz University)
RDF Knowledge Base Summarization by Inducing First-order Horn Rules
Ruoyu Wang (Shanghai Jiao Tong University)*; Daniel Sun (UNSW); Raymond K Wong (University of New South Wales)
Reducing the Planning Horizon through Reinforcement Learning
Logan Dunbar (University of Leeds)*; Benjamin Rosman (University of the Witwatersrand); Anthony G Cohn (University of Leeds); Matteo Leonetti (King’s College London)
Reinforcement Learning for Multi-Agent Stochastic Resource Collection
Niklas A Strauß (LMU Munich)*; David Winkel (LMU Munich); Max Berrendorf (Ludwig-Maximilians-Universität München); Matthias Schubert (Ludwig-Maximilians-Universität München)
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation
Zhihao Zhu (University of Science and Technology of China)*; Chenwang Wu (University of Science and Technology of China); Min Zhou (Huawei Technologies co. ltd); Hao Liao (Shenzhen University); Defu Lian (University of Science and Technology of China); Enhong Chen (University of Science and Technology of China)
Rethinking Exponential Averaging of the Fisher
Constantin O Puiu (Oxford)*
Rethinking the Misalignment Problem in Dense Object Detection
Yang Yang (Institute of Information Engineering, Chinese Academy of Sciences)*; Min Li (Institute of Information Engineering, Chinese Academy of Sciences); Bo Meng (School of Optics and Electronics, Beijing Institute of Technology); Zihao Huang (Institute of Information Engineering, Chinese Academy of Sciences); Junxing Ren (Institute of Information Engineering, Chinese Academy of Sciences); degang Sun (Institute of Information Engineering,Chinese Academy of Sciences)
SaDe: Learning Models that Provably Satisfy Domain Constraints
Kshitij Goyal (KU Leuven)*; Sebastijan Dumancic (TU Delft); Hendrik Blockeel (KU Leuven)
Safe Exploration Method for Reinforcement Learning under Existence of Disturbance
Yoshihiro Okawa (Fujitsu Limited)*; Tomotake Sasaki (Fujitsu Limited); Hitoshi Yanami (Fujitsu Limited); Toru Namerikawa (Keio University)
SAViR-T: Spatially Attentive Visual Reasoning with Transformers
Pritish Sahu (Rutgers University)*; Kalliopi Basioti (Rutgers University); Vladimir Pavlovic (Rutgers University)
Scalable Adversarial Online Continual Learning
Tanmoy Dam (University of New South Wales Canberra); mahardhika pratama (University of South Australia)*; Md Meftahul Ferdaus (A*STAR); Sreenatha Anavatti (The University of New South Wales Australia); Hussein Abbass (University of New South Wales, Australia)
SEA: Graph Shell Attention in Graph Neural Networks
Christian M.M. Frey (Christian-Albrechts-University Kiel)*; Yunpu Ma (Ludwig-Maximilians-Universität München); Matthias Schubert (Ludwig-Maximilians-Universität München)
SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting
Azqa Nadeem (Delft University of Technology)*; Sicco Verwer (Delft University of Technology)
Self-Distilled Pruning of Neural Networks
James T O’ Neill (University of Liverpool)*; Sourav Dutta (Huawei Research Centre); Haytham Assem (Huawei Research)
Self-Supervised Graph Learning with Segmented Graph Channels
Hang Gao (Institute of Software Chinese Academy of Sciences ); Jiangmeng Li (Institute of Software Chinese Academy of Sciences); Changwen Zheng (Institute of Software, Chinese Academy of Sciences)*
SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training
Qiang Huang (Jilin University)*; Jing Ma (University of Virginia); Jundong Li (University of Virginia); Huiyan Sun (Jilin University); Yi Chang (Jilin University)
Session-based Recommendation along with the Session Style of Explanation
Panagiotis Symeonidis (University of the Aegean)*; Lidija Kirjackaja (Vilnius Gediminas Technical University); Markus Zanker ()
SkipCas: Information Diffusion Prediction Model Based on Skip-gram
Dedong Ren (Heilongjiang University); Yong Liu (Heilongjiang university)*
SMACE: A New Method for the Interpretability of Composite Decision Systems
Gianluigi Lopardo (Université Côte d’Azur)*; Damien Garreau (Université Côte d’Azur); Frederic Precioso (Université Cote d’Azur); Greger Ottosson (IBM)
SMFM4L: Multi-typed Objects Multi-view Multi-instance Multi-label Learning based on Selective Matrix Factorization
Yuanlin Yang (Southwest University)*; Guangyang Han (Southwest University); Runmin Wang (Southwest University); weiwei sao (Southwest university); Baiyan Hua (Southwest University); Yuanlin Yang (Southwest University)
Sparse Horseshoe Estimation via Expectation-Maximisation
Shu Yu Tew (Monash University)*; Daniel F Schmidt (Monash University); Enes Makalic (University of Melbourne)
Spectral Ranking with Covariates
Siu Lun Chau (Department of Statistics, University of Oxford)*; Mihai Cucuringu (University of Oxford and The Alan Turing Institute); Dino Sejdinovic (University of Oxford)
Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings
Adrian Kochsiek (University of Mannheim)*; Fritz Niesel (University Mannheim); Rainer Gemulla (Universität Mannheim)
State Representation Learning for Goal-Conditioned Reinforcement Learning
Lorenzo Steccanella (UPF – Artificial Intelligence and Machine learning)*; Anders Jonsson (UPF)
STGEN: Deep Continuous-time Spatiotemporal Graph Generation
Chen Ling (Emory University)*; Hengning Cao (Cornell University); Zhao Liang (Emory University)
Stock Trading Volume Prediction with Dual-Process Meta-Learning
Ruibo Chen (Peking University)*; Wei Li (Beijing Language and Culture University); Zhiyuan Zhang (Peking University); Ruihan Bao (Mizuho Bank); Keiko Harimoto (Mizuho Bank); Xu Sun (Peking University)
Structure-preserving Gaussian Process Dynamics
Katharina Ensinger (Bosch Center for Artificial Intelligence)*; Friedrich Solowjow (RWTH Aachen University); Sebastian Ziesche (Bosch Center for Artificial Intelligence); Michael Tiemann (Bosch Center for AI); Sebastian Trimpe (RWTH Aachen University)
Structured Nonlinear Discriminant Analysis
Christopher M. A. Bonenberger (Institute for Artificial Intelligence, Ravensburg-Weingarten University of Applied Sciences)*; Wolfgang Ertel (Hochschule Ravensburg-Weingarten); Markus Schneider (Hochschule Ravensburg-Weingarten); Prof. Friedhelm Schwenker U of Ulm Germany ANN Pattern Rec. (“Respected member, IPC, ICIEV”)
Summarizing Data Structures with Gaussian Process and Robust Neighborhood Preservation
Koshi Watanabe (Hokkaido University)*; Keisuke Maeda (Hokkaido University); Takahiro Ogawa (Hokkaido University); Miki Haseyama (Hokkaido University)
Summarizing Labeled Multi-Graphs
Dimitris Berberidis (Carnegie Mellon University); Pierre Liang (Carnegie Mellon University); Leman Akoglu (CMU)*
Supervised Contrastive Learning for Few-Shot Action Classification
Hongfeng Han (Renmin University of China); Nanyi Fei (Renmin University of China); Zhiwu Lu (Renmin University of China)*; Ji-Rong Wen (Renmin University of China)
Supervised Graph Contrastive Learning for Few-shot Node Classification
Zhen Tan (Arizona State University)*; Kaize Ding (Arizona State University); Ruocheng Guo (City University of Hong Kong); Huan Liu (Arizona State University)
Team-Imitate-Synchronize for Multi-Agent Collaboration
Ronen Brafman (BGU)*; Guy Shani (Ben-Gurion University); Eliran Abdu (Ben-Gurion University); Nitsan Soffair (Ben-Gurion University)
Time constrained DL8.5 using Limited Discrepancy Search
Harold Kiossou (UCLouvain)*; Pierre Schaus (UC Louvain); Siegfried Nijssen (Université Catholique de Louvain, BE); Vinasetan Ratheil HOUNDJI (University of Abomey-Calavi)
TopoAttn-Nets: Topological Attention in Graph Representation Learning
Yuzhou Chen (Princeton University); Elena Sizikova (NYU); Yulia R. Gel (The University of Texas at Dallas)*
Training Parameterized Quantum Circuits with Triplet Loss
Christof Wendenius (Karlsruhe Institute of Technology); Eileen Kuehn (Karlsruhe Institute of Technology)*; Achim Streit (Karlsruhe Institute for Technology)
Transforming PageRank into an Infinite-Depth Graph Neural Network
Andreas Roth (TU Dortmund)*; Thomas Liebig (TU Dortmund)
Truly Unordered Probabilistic Rule Sets for Multi-class Classification
Lincen Yang (Leiden University)*; Matthijs van Leeuwen (Leiden University)
TS-MIoU: A Time Series Similarity Metric Without Mapping
Azim Ahmadzadeh (Georgia State University)*; Yang Chen (Georgia State University); Krishna Rukmini Puthucode (Georgia State University); Ruizhe Ma (University of Massachusetts Lowell); Rafal Angryk (GEORGIA STATE UNIVERSITY)
Uncertainty Awareness for Predicting Noisy Stock Price Movements
Yun-Hsuan Lien (National Yang Ming Chiao Tung University); Yu-Syuan Lin (National Yang Ming Chiao Tung University); Yu-Shuen Wang (National Yang Ming Chiao Tung University)*
Understanding Adversarial Robustness of Vision Transformers via Cauchy Problem
Zheng Wang (Exeter University)*; Wenjie Ruan (University of Exeter)
Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure
xiaoling zhou (Tianjin University); Ou Wu (Tianjin University)*; Weiyao ZHU (Center for Applied Mathematics, Tianjin University); Liang ZiYang (TianJin University)
Understanding the Benefits of Forgetting when Learning on Dynamic Graphs
Charlotte Laclau (Laboratory Hubert Curien, Univ. St-Etienne)*; Julien Tissier (Laboratory Hubert Curien, Univ. St-Etienne)
Variational Boson Sampling
Shiv Shankar (University of Massachusetts)*; Don Towsley (University of Massachusetts Amherst)
VCNet: A self-explaining model for realistic counterfactual generation
Victor V Guyomard (Orange)*; Françoise FF Fessant (Orange); Thomas Guyet (Inria, Centre de Lyon); Alexandre Termier (Inria); Tassadit Bouadi (Universite de Rennes 1)
Wasserstein t-SNE
Fynn S. Bachmann (Universität Hamburg)*; Dmitry Kobak (University of Tübingen); Philipp Hennig (University of Tübingen and MPI for Intelligent Systems, Tübingen)
Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting
Kiran Madhusudhanan (University of Hildesheim)*; Johannes Burchert (University of Hildesheim); Nghia Duong-Trung (Technische Universität Berlin); Stefan Born (Technische Universität Berlin); Lars Schmidt-Thieme (University of Hildesheim)

Accepted Papers in Applied Data Science Track

‘John ate 5 apples’ != ‘John ate some apples’: Self-Supervised Paraphrase Quality Detection for Algebraic Word Problems
Rishabh Gupta (IIIT Delhi)*; Venktesh V (Indraprastha Institute of Information Technology); Mukesh Mohania (IIIT Delhi); Vikram Goyal (“IIIT Delhi, India”)
A Bayesian Markov Model for Station-Level Origin-Destination Matrix Reconstruction
Victor Amblard (CITiO); Amir Dib (CITIO); Noëlie Cherrier (CITiO)*; Guillaume Barthe (CITiO)
A Pre-Screening Approach for Faster Bayesian Network Structure Learning
Thibaud Rahier (Criteo AI Lab)*; Sylvain Marie (Schneider Electric); Florence B.P. Forbes (Inria)
A prescriptive machine learning approach for assessing goodwill in the automotive domain
Stefan Haas (BMW)*; Eyke Hüllermeier (University of Munich)
A Recommendation System for CAD Assembly Modeling based on Graph Neural Networks
Carola Gajek (University of Augsburg)*; Alexander Schiendorfer (Technische Hochschule Ingolstadt); Wolfgang Reif (University of Augsburg)
An Improved Yaw Control Algorithm for Wind Turbines via Reinforcement Learning
Alban Puech (Ecole Polytechnique )*; Jesse Read (Ecole Polytechnique)
Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization
Zheng Chen (Osaka univerisity)*; Lingwei Zhu (NAIST); Ziwei Yang (NAIST); Takashi Matsubara (Osaka University)
Automatic Feature Engineering through Monte CarloTree Search
Yiran Huang (Karlsruhe Institute of Technology)*; Yexu Zhou (KIT); Michael Hefenbrock (TECO); Till Riedel (KIT); Likun Fang (KIT); Michael Beigl
Automatic Grading of Student Code with Similarity Measurement
Dongxia Wang (East China Normal University); En Zhang (East China Normal University); Xuesong Lu (East China Normal University)*
Banksformer: A Deep Generative Model for Synthetic Transaction Sequences
Kyle L Nickerson (Memorial University of Newfoundland)*; Terrence Tricco (Memorial University of Newfoundland); Antonina Kolokolova (Memorial University); Farzaneh Shoeleh (Verafin); Charles Robertson (Verafin Inc); John Hawkin (Verafin); Ting Hu (Queen’s University)
Bayesian Multi-Head Convolutional Neural Networks with Bahdanau Attention for Forecasting Daily Precipitation in Climate Change Monitoring
Firas Gerges (New Jersey Institute of Technology)*; Michel C. Boufadel (New Jersey Institute of Technology); Elie Bou-Zeid (Princeton University); Ankit Darekar (New Jersey Institute of Technology); Hani Nassif (Rutgers University – New Brunswick); Dr. Jason T. L. Wang (New Jersey Institute of Technology)
Bi-matching Mechanism to Combat Long-tail Senses of Word Sense Disambiguation
Junwei Zhang (Tianjin University)*; Ruifang He (Tianjin University); Fengyu Guo (Tianjin Normal University)
Block-Level Surrogate Models for Latency Estimation in Hardware-Aware Neural Architecture Search
Kurt H. W. Stolle (Eindhoven University of Technology ); Sebastian Vogel (NXP Semiconductors); Fons van der Sommen (Dept. Electrical Engineering, Eindhoven University of Technology, Eindhoven, NL); Willem P Sanberg (NXP Semiconductors)*
BusWTE: Realtime Bus Waiting Time Estimation of GPS Missing via Multi-Task Learning
yuecheng rong (Baidu)*; Jun Liu (Xi’an Jiaotong University); Zhilin Xu (Baidu); Jian Ding (Baidu); Chuanming Zhang (Baidu); Jiaxiang Gao (Baidu)
Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems
Tom A Mertens (Tu/e); Marwan Hassani (TU Eindhoven)*
CGPM:Poverty Mapping Framework based on Multi-Modal Geographic Knowledge Integration and Macroscopic Social Network Mining
Geng Zhao (JINAN University)*; Ziqing Gao (Xi’an Jiaotong University); ChiHsu Tsai (Jinan University); Jiamin Lu (Jinan University)
Contextualized Graph Embeddings for Adverse Drug Event Detection
Ya Gao (Aalto University); Shaoxiong Ji (Aalto Universtiy)*; Tongxuan Zhang (Tianjin Normal University); Prayag Tiwari (Aalto University, Finland); Pekka Marttinen (Aalto University)
Coupling User Preference with External Rewards to Enable Driver-centered and Resource-aware EV Charging Recommendation
Chengyin Li (Wayne State University); Zheng Dong (Wayne State University); Nathan Fisher (Wayne State University); Dongxiao Zhu (Wayne State Unversity, USA)*
Cubism: Co-Balanced Mixup for Unsupervised Volcano-Seismic Knowledge Transfer
Mahsa Keramati (Simon Fraser University)*; Mohammad Tayebi (Simon Fraser University); Zahra Zohrevand (Simon Fraser University); Uwe Glässer (SFU); Juan Anzieta (Simon Fraser University); Glyn Williams-Jones (Simon Fraser University)
Deep Active Learning for Detection of Mercury’s Bow Shock and Magnetopause Crossings
Sahib Julka (University of Passau)*; Nikolas Kirschstein (University of Passau); Michael Granitzer (University of Passau); Alexander Lavrukhin (M.V.Lomonosov Moscow State University); Ute V Amerstorfer (Space Research Institute, Austrian Academy of Sciences)
Detection of ADHD based on Eye Movements during Natural Viewing
Shuwen Deng (University of Potsdam)*; Paul Prasse (University of Potsdam); David R Reich (Universität Potsdam); Sabine Dziemian (University of Zurich); Maja Stegenwallner-Schütz (University of Potsdam); Daniel Krakowczyk (Universität Potsdam); Silvia Makowski (University of Potsdam); Nicolas Langer (University of Zurich); Tobias Scheffer (University of Potsdam); Lena A. Jäger (University of Potsdam)
Exploring Graph-aware Multi-View Fusion for Rumor Detection on Social Media
Yang Wu (Institute of Information Engineering, Chinese Academy of Sciences)*; Jing Yang (Institute of Information Engineering, Chinese Academy of Sciences); Xiaojun Zhou (School of Cyber Security, University of Chinese Academy of Sciences;State Key Laboratory of Information Security, Institute of Information Engineering,Chinese Academy of Sciences); Liming Wang (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences); Zhen Xu (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences)
Factorized Structured Regression for Large-Scale Varying Coefficient Models
David Ruegamer (LMU Munich)*; Andreas Bender (LMU Munich); Simon Wiegrebe (LMU Munich); Daniel Racek (LMU Munich); Bernd Bischl (LMU Munich); Christian L. Müller (Center for Computational Mathematics, Flatiron Institute); Clemens Stachl (University St. Gallen)
FFBDNet: Feature Fusion and Bipartite Decision Networks for Recommending Medication Combination
Zisen Wang (Institute of Computing Technology, Chinese Academy of Sciences); Ying Liang (Institute of Computing Technology, Chinese Academy of Sciences)*; Zhengjun Liu (Institute of Computing Technology, Chinese Academy of Sciences)
GALG: Linking Addresses in Tracking Ecosystem Using Graph Autoencoder with Link Generation
Tianyu Cui (Institute of Information Engineering)*; gang xiong (Institute of Information Engineering,Chinese Academy of Sciences); Chang Liu (Institute of Information Engineering, CAS); Junzheng Shi (Institute of Information Engineering,Chinese Academy of Sciences); peipei fu ( Institute of Information Engineering, CAS); Gaopeng Gou (Institute of Information Engineering, CAS)
Go green: A decision-tree framework to select optimal box-sizes for product shipments
Karthik S Gurumoorthy (Amazon)*; Abhiraj Hinge (Amazon)
Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting
Alexander Koebler (Siemens AG)*; Ralf Gross (Siemens AG); Florian Buettner (German Cancer Research Center and Frankfurt University); Ingo Thon (Siemens AG)
Improving Micro-video Recommendation by Controlling Position Bias
Yisong Yu (Institute of Software Chinese Academy of Sciences); Beihong Jin (Institute of Software, Chinese Academy of Sciences)*; Jiageng Song (Institute of Software Chinese Academy of Sciences); Beibei Li (Institute of Software Chinese Academy of Sciences); Yiyuan Zheng (Institute of Software Chinese Academy of Sciences); Wei Zhuo (MX Media Co., Ltd)
Interpretations of Predictive Models for Lifestyle-related Diseases at Multiple Time Intervals
Yuki OBA (University of Tsukuba)*; Taro TEZUKA (University of Tsukuba); Masaru SANUKI (University of Tsukuba); Yukiko WAGATSUMA (University of Tsukuba)
Is this bug severe? A text-cum-graph based model for bug severity prediction
Rima Hazra (IIT Kharagpur)*; Arpit Dwivedi (Indian Institute of Technology Kharagpur); Animesh Mukherjee (IIT Kharagpur)
Looking Beyond the Past: Analyzing the Intrinsic Playing Style of Soccer Teams
Jeroen Clijmans (KU Leuven); Maaike Van Roy (KU Leuven)*; Jesse Davis (KU Leuven)
MepoGNN: Metapopulation Epidemic Forecasting with Graph Neural Networks
Qi CAO (The University of Tokyo)*; Renhe Jiang (The University of Tokyo); Chuang Yang (The University of Tokyo); Zipei Fan (University of Tokyo); Xuan Song (The University of Tokyo); Ryosuke Shibasaki (University of Tokyo)
Meta Hierarchical Reinforced Learning to Rank for Recommendation: A Comprehensive Study in MOOCs
Yuchen Li (Shanghai Jiao Tong University)*; Haoyi Xiong (Baidu Research); Linghe Kong (Shanghai Jiao Tong University); Rui Zhang (Shanghai Jiao Tong University); Dejing Dou (Baidu); Guihai Chen (Shanghai Jiao Tong University)
MULTIFORM: Few-Shot Knowledge Graph Completion via Multi-Modal Contexts
Xuan Zhang (Renmin University of China)*; Xun Liang (Renmin University of China); Xiangping Zheng (Renmin University of China); Bo Wu (Renmin University of China); Yuhui Guo (Renmin University of China)
MultiLayerET: A Unified Representation of Entities and Topics Using Multilayer Graphs
Jumanah Alshehri (Temple Univesrity)*; Zoran Obradovic (Temple University); Eduard Dragut (Temple Univ.); Marija Stanojevic (Temple University); Parisa Khan (Temple University); Benjamin Rapp (Temple University)
Near out-of-distribution detection for low-resolution radar micro-Doppler signatures
Martin Bauw (MINES ParisTech)*; Santiago Velasco-Forero (MINES ParisTech); Jesus Angulo (Mines Paris Tech); Claude Adnet (Thales LAS France); Olivier Airiau (Thales LAS France)
Neural Networks with Feature Attribution and Contrastive Explanations
Housam Babiker (Department of Computing Science, University of Alberta)*; Mi-Young Kim (University of Alberta); Randy Goebel (University of Alberta)
PathOracle: A Deep Learning Based Trip Planner for Daily Commuters
Md. Tareq Mahmood (Bangladesh University of Engineering and Technology (BUET))*; Mohammed Eunus Ali (Bangladesh University of Engineering and Technology (BUET)); Muhammad Aamir Cheema (Monash University); Syed Md. Mukit Rashid (Bangladesh University of Engineering and Technology (BUET)); Timos Sellis (Athena Research Center)
Placing (Historical) Facts on a Timeline: A Classification cum Co-ref Resolution Approach
Sayantan Adak (IIT Kharagpur)*; Altaf Ahmad (IIT Kharagpur); Aditya Basu (IIT Kharagpur); Animesh Mukherjee (IIT Kharagpur)
Recognizing Cognitive Load by a Hybrid Spatio-Temporal Causal Model from Multivariate Physiological Data
Zirui Yong (Chongqing University); Li Liu (Chongqing University)*; Guoxin Su (University of Wollongong); Xiaohu Li (Chongqing University); Lingyun Sun (Zhejiang University); Zejian Li (Zhejiang University)
Recognizing Non-Small Cell Lung Cancer Subtypes by a Constraint-Based Causal Network from CT Images
Zhengqiao Deng (Chongqing University); Shuang Qian (Chongqing University); Jing Qi (Tianjin Medical University Cancer Institute and Hospital); Li Liu (Chongqing University)*; Bo Xu (Tianjin Medical University Cancer Institute and Hospital, Chongqing University Cancer Hospital)
Recommending Related Products Using Graph Neural Networks in Directed Graphs
Srinivas Virinchi (Amazon )*; Anoop Saladi (amazon); Abhirup Mondal (Amazon)
Risk-Aware Reinforcement Learning for Multi-Period Portfolio Selection
David Winkel (LMU Munich)*; Niklas A Strauß (LMU Munich); Matthias Schubert (Ludwig-Maximilians-Universität München); Thomas Seidl (LMU Munich)
Route to Time and Time to Route: Travel Time Estimation from Sparse Trajectories
Zhiwen Zhang (The University of Tokyo); Hongjun Wang (Southern University of Science and Technology); Jiyuan Chen (Southern University of Science and Technology); Zipei Fan (University of Tokyo)*; Xuan Song (Southern University of Science and Technology); Ryosuke Shibasaki ()
Securing Cyber-Physical Systems: Physics-Enhanced Adversarial Learning for Autonomous Platoons
Guoxin Sun (The University of Melbourne)*; Tansu Alpcan (University of Melbourne); Benjamin Rubinstein (Melbourne); Seyit Camtepe (CSIRO Data61)
Submodular Meta Data Compiling for Meta Optimization
Fengguang Su (Tianjin University)*; Yu Zhu (Tianjin University); Ou Wu (Tianjin University); Yingjun Deng (Tianjin University )
The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users during the COVID-19 Pandemic
Ninghan Chen (The University of Luxembourg); Xihui Chen (University of Luxembourg)*; Zhiqiang ZHONG (University of Luxembourg); Jun Pang (University of Luxembourg)
Towards Federated COVID-19 Vaccine Side Effect Prediction
Jiaqi Wang (Penn State University)*; Cheng Qian (IQVIA); Suhan Cui (Pennsylvania State University); Lucas Glass (IQVIA); Fenglong Ma (Pennsylvania State University)
TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification
Zhaobin Mo (Columbia University); Yongjie Fu (Columbia University); Daran Xu (Columbia University); Xuan Di (Columbia University)*
Trigger Detection for the sPHENIX Experiment via Bipartite Graph Networks with Set Transformer
Tingting Xuan (Stony Brook University)*; Giorgian Borca-Tasciuc (Stony Brook University); Yimin Zhu (Stony Brook University); Yu Sun ( Sunrise Technology Inc.); Cameron Dean ( Los Alamos National Laboratory); Zhaozhong Shi ( Los Alamos National Laboratory); Dantong Yu (New Jersey Institute of Technology)
UrbanAnom: An Approach to Predict Urban Anomaly from Multi-Stream Data
Bhumika . (IIT Jodhpur)*; Debasis Das (Indian Institute of technology(IIT) Jodhpur)
Vec2Node: Self-training with Tensor Augmentation for Text Classification with Few Labels
Sara Abdali (University of California, Riverside )*; Subhabrata Mukherjee (Microsoft Research); Evangelos Papalexakis (UC Riverside)
Waypoint Generation in Row-based Crops with Deep Learning and Contrastive Clustering
Francesco Salvetti (Politecnico di Torino)*; Simone Angarano (Politecnico di Torino); Mauro Martini (Politecnico di Torino); Simone Cerrato (Politecnico di Torino); Marcello Chiaberge (Politecnico di torino)