PhD Forum

The PhD forum will take place in room Palladium 2, Minatec, on Monday morning, according to the (tentative) schedule below.

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)


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