Login Paper Search My Schedule Paper Index Help

My ICASSP 2020 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)
Click on the icon to view the manuscript on IEEE XPlore in the IEEE ICASSP 2020 Open Preview.

Clicking on the Add button next to a paper title will add that paper to your custom schedule.
Clicking on the Remove button next to a paper will remove that paper from your custom schedule.

TU1.I: Machine Learning for Communcations I

Session Type: Poster
Time: Tuesday, 5 May, 11:30 - 13:30
Location: On-Demand
Session Chairs: Osvaldo Simeone, King's College London and Joakim Jaldén, KTH Royal Institute of Technology
 
   TU1.I.1: COMPLEX TRAINABLE ISTA FOR LINEAR AND NONLINEAR INVERSE PROBLEMS
         Satoshi Takabe; Nagoya Institute of Technology
         Tadashi Wadayama; Nagoya Institute of Technology
         Yonina Eldar; Weizmann Institute of Science
 
   TU1.I.2: CONDITIONAL MUTUAL INFORMATION NEURAL ESTIMATOR
         Sina Molavipour; KTH Royal Institute of Technology
         Germán Bassi; KTH Royal Institute of Technology
         Mikael Skoglund; KTH Royal Institute of Technology
 
   TU1.I.3: Q-LEARNING BASED PREDICTIVE RELAY SELECTION FOR OPTIMAL RELAY BEAMFORMING
         Anastasios Dimas; Rutgers University
         Konstantinos Diamantaras; International Hellenic University
         Athina Petropulu; Rutgers University
 
   TU1.I.4: PEER TO PEER OFFLOADING WITH DELAYED FEEDBACK: AN ADVERSARY BANDIT APPROACH
         Miao Yang; ShanghaiTech University
         Hongbin Zhu; ShanghaiTech University
         Haifeng Wang; Shanghai Institute of Microsystem and Information Technology
         Yevgeni Koucheryavy; Tampere University
         Konstantin Samouylov; Peoples' Friendship University of Russia
         Hua Qian; Shanghai Advanced Research Institute, Chinese Academy of Sciences
 
   TU1.I.5: TRANSFERABLE POLICIES FOR LARGE SCALE WIRELESS NETWORKS WITH GRAPH NEURAL NETWORKS
         Mark Eisen; Intel Corporation
         Alejandro Ribeiro; University of Pennsylvania
 
   TU1.I.6: A ZEROTH-ORDER LEARNING ALGORITHM FOR ERGODIC OPTIMIZATION OF WIRELESS SYSTEMS WITH NO MODELS AND NO GRADIENTS
         Dionysios Kalogerias; University of Pennsylvania
         Mark Eisen; Intel Corporation
         George Pappas; University of Pennsylvania
         Alejandro Ribeiro; University of Pennsylvania
 
   TU1.I.7: JOINT SPARSE RECOVERY USING DEEP UNFOLDING WITH APPLICATION TO MASSIVE RANDOM ACCESS
         Anand P. Sabulal; Indian Institute of Technology Madras
         Srikrishna Bhashyam; Indian Institute of Technology Madras
 
   TU1.I.8: LEARNING-BASED CONTENT CACHING AND USER CLUSTERING: A DEEP DETERMINISTIC POLICY GRADIENT APPROACH
         Kun-Lin Chan; National Chiao Tung University
         Feng-Tsun Chien; National Chiao Tung University
 
   TU1.I.9: LEARNING-AIDED CONTENT PLACEMENT IN CACHING-ENABLED FOG COMPUTING SYSTEMS USING THOMPSON SAMPLING
         Junge Zhu; ShanghaiTech University
         Xi Huang; ShanghaiTech University
         Ziyu Shao; ShanghaiTech University
 
   TU1.I.10: JOINT CODING AND MODULATION IN THE ULTRA-SHORT BLOCKLENGTH REGIME FOR BERNOULLI-GAUSSIAN IMPULSIVE NOISE CHANNELS USING AUTOENCODERS
         Kirty Vedula; Worcester Polytechnic Institute
         Randy Paffenroth; Worcester Polytechnic Institute
         D. Richard Brown III; Worcester Polytechnic Institute
 
   TU1.I.11: DEEP JOINT SOURCE-CHANNEL CODING FOR WIRELESS IMAGE RETRIEVAL
         Mikolaj Jankowski; Imperial College London
         Deniz Gündüz; Imperial College London
         Krystian Mikolajczyk; Imperial College London
 
   TU1.I.12: META-LEARNING TO COMMUNICATE: FAST END-TO-END TRAINING FOR FADING CHANNELS
         Sangwoo Park; Korea Advanced Institute of Science and Technology (KAIST)
         Osvaldo Simeone; King’s College London
         Joonhyuk Kang; Korea Advanced Institute of Science and Technology (KAIST)