SiG-DML-P5: Adaptive, Federated and Trustwothy Learning
Thu, 11 Sep, 15:30 - 17:10 Italy Time (UTC +2)
Location: Poster Area D
Session Type: Poster
Session Chair: Pietro Zanuttigh, University of Padova
Track: SiG-DML - Signal and Data Analytics for Machine Learning

SiG-DML-P5.1: DATA-DRIVEN FUZZY LOGIC APPROACH FOR INPUT ADMITTANCE ESTIMATION IN GRID-TIED INVERTERS
Kamran Sabahi, Aalborg university, Denmark; Jesper Rindom Jensen, Yang Wu, Xiongfei Wang, Mads Græsbøll Christensen, Aalborg University, Denmark

SiG-DML-P5.2: Learning to Sort in Continuous Spaces: Neural Architectures and Iterative Training Strategies
Matthieu CORNU, ENS Paris-Saclay, France; Cyrille ENDERLI, Thales DMS, France; Thomas RODET, ENS Paris-Saclay, France

SiG-DML-P5.3: Adaptive Local Training in Federated Learning
Donald Shenaj, University of Padova, Italy; Eugene Belilovsky, Concordia University, Italy; Pietro Zanuttigh, University of Padova, Italy

SiG-DML-P5.4: Graph Transfer Learning-Based Attack Detection in Cyber-Physical Water Distribution Systems
Md Rakibul Ahasan, Faaiz Joad, Florida State University, United States; Rachad Atat, Lebanese American University, Lebanon; Coleman Thompson, Florida State University, United States; Erchin Serpedin, Texas A&M University, United States; Abdulrahman Takiddin, Florida State University, United States

SiG-DML-P5.5: Trustworthy Efficient Communication for Distributed Learning using LQ-SGD Algorithm
Hongyang Li, University of Luxembourg, Luxembourg; Lincen Bai, University of Paris-Saclay, France; Caesar Wu, University of Luxembourg, Luxembourg; Mohammed Chadli, Said Mammar, University of Paris-Saclay, France; Pascal Bouvry, University of Luxembourg, Luxembourg

SiG-DML-P5.6: TOWARDS POINT CLOUD COUNTERFACTUAL EXPLANATIONS
Nicolas Vercheval, Aleksandra Pizurica, Ghent University, Belgium

SiG-DML-P5.7: LATENT BEHAVIOR CLONING FOR DEEP REINFORCEMENT LEARNING ROBOTIC TASKS
Romanos Voulgarakis, Dimitrios Katsikas, Nikolaos Passalis, Anastasios Tefas, Aristotle University of Thessaloniki, Greece

SiG-DML-P5.8: Mean-Field Multi-Agent Learning: A Trust Region Approach
Antonio Ocello, Lorenzo Mancini, Safwan Labbi, Daniil Tiapkin, École polytechnique, Institut Polytechnique de Paris, France; Adel Belouchrani, École Nationale Polytechnique, France; Éric Moulines, École polytechnique, Institut Polytechnique de Paris, France