Technical Program

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MLSP-P10: Learning Methods

Session Type: Poster
Time: Thursday, 7 May, 09:00 - 11:00
Location: On-Demand
Virtual Session: View on Virtual Platform
Session Chairs: Ercan Kuruoglu, Tsinghua-Berkeley Shenzhen Institute and Fedorov Igor, ARM
 
 MLSP-P10.1: LEARNING DIVERSE SUB-POLICIES VIA A TASK-AGNOSTIC REGULARIZATION ON ACTION DISTRIBUTIONS.
         Liangyu Huo; Beihang University
         Zulin Wang; Beihang University
         Mai Xu; Beihang University
         Yuhang Song; University of Oxford
 
 MLSP-P10.2: FEDERATED LEARNING WITH MUTUALLY COOPERATING DEVICES: A CONSENSUS APPROACH TOWARDS SERVER-LESS MODEL OPTIMIZATION
         Stefano Savazzi; Consiglio Nazionale delle Ricerche CNR-IEIIT
         Monica Nicoli; Politecnico di Milano
         Vittorio Rampa; Consiglio Nazionale delle Ricerche CNR-IEIIT
         Sanaz Kianoush; Consiglio Nazionale delle Ricerche CNR-IEIIT
 
 MLSP-P10.3: NO-REGRET NON-CONVEX ONLINE META-LEARNING
         Zhenxun Zhuang; Boston University
         Yunlong Wang; IQVIA Inc.
         Kezi Yu; IQVIA Inc.
         Songtao Lu; IBM
 
 MLSP-P10.4: ASYNCHROUNOUS DECENTRALIZED LEARNING OF A NEURAL NETWORK
         Xinyue Liang; KTH Royal Institute of Technology
         Alireza M. Javid; KTH Royal Institute of Technology
         Mikael Skoglund; KTH Royal Institute of Technology
         Saikat Chatterjee; KTH Royal Institute of Technology
 
 MLSP-P10.5: LEARNING PERCEPTION AND PLANNING WITH DEEP ACTIVE INFERENCE
         Ozan Çatal; Ghent University - imec
         Tim Verbelen; Ghent University - imec
         Johannes Nauta; Ghent University - imec
         Cedric De Boom; Ghent University - imec
         Bart Dhoedt; Ghent University - imec
 
 MLSP-P10.6: PROJECTION FREE DYNAMIC ONLINE LEARNING
         Deepak Singh Kalhan; Indian Institute of Technology Kanpur
         Amrit Singh Bedi; U.S. Army Research Laboratory
         Alec Koppel; U.S. Army Research Laboratory
         Ketan Rajawat; Indian Institute of Technology Kanpur
         Abhishek Kumar Gupta; Indian Institute of Technology Kanpur
         Adrish Banerjee; Indian Institute of Technology Kanpur
 
 MLSP-P10.7: LEARNING PARTIAL DIFFERENTIAL EQUATIONS FROM DATA USING NEURAL NETWORKS
         Ali Hasan; Duke University
         João M. Pereira; Duke University
         Robert Ravier; Duke University
         Sina Farsiu; Duke University
         Vahid Tarokh; Duke University
 
 MLSP-P10.8: ACTIVE LEARNING WITH UNSUPERVISED ENSEMBLES OF CLASSIFIERS
         Panagiotis Traganitis; University of Minnesota
         Dimitrios Berberidis; Carnegie Mellon University
         Georgios B. Giannakis; University of Minnesota
 
 MLSP-P10.9: NASIL : NEURAL ARCHITECTURE SEARCH WITH IMITATION LEARNING
         Farzaneh S. Fard; Fluent.ai
         Arash Rad; Fluent.ai
         Vikrant Singh Tomar; Fluent.ai
 
 MLSP-P10.10: MULTI-VIEW CLUSTERING VIA MIXED EMBEDDING APPROXIMATION
         Danyang Wu; Northwestern Polytechnical University
         Feiping Nie; Northwestern Polytechnical University
         Rong Wang; Northwestern Polytechnical University
         Xuelong Li; Northwestern Polytechnical University
 
 MLSP-P10.11: SIGNAL CLUSTERING WITH CLASS-INDEPENDENT SEGMENTATION
         Stefano Gasperini; Technische Universität München
         Magdalini Paschali; Technische Universität München
         Carsten Hopke; Airbus Defence and Space GmbH
         David Wittmann; Airbus Defence and Space GmbH
         Nassir Navab; Technische Universität München