PhD Forum

The PhD forum will take place in room Palladium 2, Minatec, on Monday morning, according to the (tentative) schedule below. More information on how to going to Minatec from WTC are provided here.

All conference participants are welcome to join!

09:00–09:07 Opening words
09:07–09:20 Group mentors: Joao Gama and Marc Plantevit
On the Generalization of Neural Combinatorial Optimization Heuristics, by Sahil Manchanda (IIT Delhi)*; Sofia Michel (Naverlabs Europe); Darko Drakulic (Naverlabs Europe); Jean-Marc Andreoli (Naverlabs Europe) (2 min)
Detecting Anomalies with Autoencoders on Data Streams, by Lucas Cazzonelli (FZI Research Center for Information Technology)* (2 min)
Learning the energy of matter with neural networks: selection of atomic features with the adaptive group lasso, by Johannes E Sandberg (Grenoble INP)* (6 min)
Discussion (3 min)
09:20–09:33 Group mentors: Giuseppe Manco and Jan Ramon
Supervised Graph Contrastive Learning for Few-shot Node Classification, by Zhen Tan (Arizona State University)* (2 min)
Adversarial Projections to Tackle Support-Query Shifts in Few-Shot Meta-Learning, by Aroof Aimen (Indian Institute of Techology, Ropar)*; Bharat Ladrecha (Indian Institute of Technology Ropar); Narayanan C Krishnan (IIT Palakkad) (2 min)
Graph-Survival: A Survival Analysis Framework for Machine Learning on Temporal Networks, by Raphaël Romero (Ghent University)* (6 min)
Discussion (3 min)
09:33–09:50 Group mentors: Toon Calders and Elisa Fromont
Learning to Teach Fairness-aware Deep Multi-Task Learning, by Arjun Roy (L3S Research Center)*; Eirini Ntoutsi (Freie Universität Berlin) (2 min)
Envy-free recommendation, by Nan Li (Ghent University)*; Bo Kang (Ghent University); Jefrey Lijffijt (Ghent University); Tijl De Bie (Ghent University) (6 min)
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent, by Paul Mangold (INRIA)*; Aurélien Bellet (INRIA); Joseph Salmon (Université de Montpellier); Marc Tommasi (Lille University) (6 min)
Discussion (3 min)
09:50–10:13 Group mentors: Neil Hurley and Georgiana Ifrim
A Recommendation System for CAD Assembly Modeling based on Graph Neural Networks, by Carola Gajek (University of Augsburg)*; Alexander Schiendorfer (Technische Hochschule Ingolstadt); Wolfgang Reif (University of Augsburg) (2 min)
Recommendation system infrastructure for the energy efficiency of buildings, by Loup-Noé Lévy (UVSQ)*; Guillaume Guerard (ESILV); Soufian Ben Amor (UVSQ) (6 min)
Automated learning in challenging scenarios, by prabhant singh (TU Eindhoven)* (6 min)
Collaborative learning for the reduction of test logs and the prediction of anomalies on monitoring logs, by Bahareh Afshinpour (Grenoble INP- LIG Lab)* (6 min)
Discussion (3 min)
10:13–10:30 Group mentors: Bo Kang and Thomas Gärtner
A Non-Parametric Bayesian Approach for Uplift Discretization and Feature Selection, by Mina RAFLA (Orange Labs)*; nicolas Voisine (Orange); Bruno Cremilleux (Université de Caen Normandie); Marc Boulle (Orange Labs) (2 min)
Imputation of MNAR values in high dimensional proteogenomics datasets, by Lucas Etourneau (Université Grenoble-Alpes)*; Thomas Burger (CNRS); Nelle Varoquaux (CNRS); Laura Fancello (Laboratoire de Biologie Medicale Multisite AURAGEN) (6 min)
Understanding dynamic sparse training capabilities in accommodating sparse data, by Işıl I Baysal Erez (University of Twente)* (6 min)
Discussion (3 min)

Break

11:00–11:17 Group mentors: Mykola Pechenizkiy and Albrecht Zimmermann
VCNet: A self-explaining model for realistic counterfactual generation, by Victor V Guyomard (Orange)*; Thomas Guyet (Inria, Centre de Lyon); Tassadit Bouadi (Universite de Rennes 1); Alexandre Termier (Université Rennes 1); Françoise FF Fessant (Orange) (2 min)
Work in Progress: An Explainable Conversational Search System, by Tolga Akar (Technische Universität Berlin)* (6 min)
Informing Machine Learning Models by Refined Expert Rules, by Alexander Koebler (Siemens AG)*; Ingo Thon (Siemens AG); Ralf Gross (Siemens AG); Florian Buettner (German Cancer Research Center and Frankfurt University) (6 min)
Discussion (3 min)
11:17–11:32 Group mentors: Nicolas Kourtellis and Maguelonne Teisseire
Breiman trees for active learning in regression, by Ashna Jose (Grenoble INP)*; João Paulo Almeida de Mendonça (Grenoble INP); Emilie Devijver (Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP*, LIG, 38000 Grenoble); Noël Jakse (Univ. Grenoble Alpes, CNRS, Grenoble INP, SIMaP, F-38000 Grenoble); Velérie Monbet (University of Rennes I); Roberta Poloni (Univ. Grenoble Alpes, CNRS, Grenoble INP, SIMaP, F-38000 Grenoble ) (6 min)
A Holonic Smart Grid Model for Isolated Areas, by Ihab TALEB (ESILV)*; Guillaume Guerard (ESILV); Frédéric FAUBERTEAU (ESILV); Nga NGUYEN (ESILV) (6 min)
Discussion (3 min)
11:32–11:49 Group mentors: Jefrey Lijffijt and Sibylle Hess
SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting, by Azqa Nadeem (Delft University of Technology)*; Sicco Verwer (Delft University of Technology) (2 min)
Understanding the sensitivity of convolutional neural networks to Gaussian image perturbations with the spectral bias, by Gabriel Kasmi (Mines Paris – PSL)*; Laurent Dubus (RTE France); Philippe Blanc (Mines ParisTech); Yves-Marie Saint-Drenan (Mines Paris – PSL) (6 min)
How to securely shuffle? A survey about Secure Shufflers for Federated Learning, by Marc DAMIE (Inria)*; Florian Hahn (University of Twente); Andreas Peter (University of Oldenburg); Jan Ramon (INRIA, FR) (6 min)
Discussion (3 min)
11:49–12:08 Group mentors: Zhaochun Ren, Celine Robardet and Fabio Pinelli
Near OOD detection for low-resolution radar micro-Doppler signatures, by Martin Bauw (MINES ParisTech)* (2 min)
Wasserstein t-SNE, by Fynn S. Bachmann (Universität Hamburg)* (2 min)
AIDA-Vis: Automatic Data Visualiation with Human Preferences, by Walter Laurito (FZI)*; Steffen Thoma (FZI Research Center for Information Technology); Jonas Lachowitzer (Disy) (6 min)
Non-linear Motion Transformers for Video Frame Interpolation, by Sasmita Pandey (NISER)*; Subhankar Mishra (NISER) (6 min)
Discussion (3 min)
12:08–12:25 Group mentors: Andrea Passerini and Ulf Brefeld
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient, by Jan-Philipp Schulze (Fraunhofer AISEC)*; Philip Sperl (Fraunhofer AISEC); Ana Radutoiu (Technische Universität München); Carla Christin Sagebiel (Fraunhofer AISEC); Konstantin Böttinger (Fraunhofer AISEC) (2 min)
Reducing Graph Imbalance by Adding Links, by yoosof mashayekhi (Ghent University)*; Bo Kang (Ghent University); Jefrey Lijffijt (Ghent University); Tijl De Bie (Ghent University) (6 min)
Neural-Symbolic Integration of Knowledge Extraction and Reasoning on Graph Data, by Luisa Werner (INRIA Grenoble)* (6 min)
Discussion (3 min)
12:25–13:00 Closing discussion

Because they can be in a preliminary stage and not always ready for wide public dissemination, access to the articles for work-in-progress contributions is restricted (username: ecmlpkdd, password: JuglansL).