Intersection of Information Theory and Signal Processing: New Signal Models, their Information Content and Acquisition Complexity
Videos from BIRS Workshop
Venkat Chandrasekaran, California Institute of Technology
Monday Oct 29, 2018 09:03 - 10:04
Learning Regularizers from Data
Arian Maleki, Columbia University
Monday Oct 29, 2018 10:30 - 11:02
Comparing Signal Recovery Algorithms: Phase Transition Analysis and Beyond
Aaron Berk, University of British Columbia
Monday Oct 29, 2018 11:03 - 11:34
Parameter instability regimes in proximal denoising
John Murray-Bruce, Boston University
Monday Oct 29, 2018 14:33 - 15:05
Beyond Binomial and Negative Binomial: Adaptation in Bernoulli Parameter Estimation
Alon Kipnis, Stanford University
Monday Oct 29, 2018 15:31 - 16:42
Information efficient data acquisition using analog to digital compression
Wenda Zhou, Columbia University
Monday Oct 29, 2018 16:47 - 17:18
Compressed Sensing in the Presence of Speckle Noise
Michelle Effros, California Institute of Technology
Tuesday Oct 30, 2018 09:08 - 10:11
On a New Approach to Random Access Communication
Armeen Taeb, California Institute of Technology
Tuesday Oct 30, 2018 10:32 - 11:01
False Discovery and Its Control in Low Rank Estimation
Eric Lybrand, University of California San Diego
Tuesday Oct 30, 2018 11:05 - 11:31
Quantization for Low-Rank Matrix Recovery
Ozgur Yilmaz, University of British Columbia
Tuesday Oct 30, 2018 13:32 - 14:31
Near-optimal sample complexity for convex tensor completion
Xiaowei Li, University of British Columbia
Tuesday Oct 30, 2018 14:32 - 14:57
Concentration for Euclidean Norm of Random Vectors
Nir Shlezinger, Technion
Tuesday Oct 30, 2018 15:30 - 16:02
Hardware-limited task-based quantization.
Kaiming Shen, University of Toronto
Tuesday Oct 30, 2018 16:03 - 16:31
Fractional Programming for Communication Systems
Wei Yu, University of Toronto
Tuesday Oct 30, 2018 16:32 - 17:02
Spatial Deep Learning for Wireless Scheduling
Lizhong Zheng, Massachusetts Institute of Technology
Wednesday Oct 31, 2018 09:02 - 10:10
Local Geometric Analysis and Applications to Learning Algorithms.
Miguel Rodrigues, University College of London
Wednesday Oct 31, 2018 10:32 - 11:04
On Deep Learning for Inverse Problems
Salman Salamatian, Massachusetts Institute of Technology
Wednesday Oct 31, 2018 11:07 - 11:39
Principal Inertia Components & Applications
Shirin Jalali, Nokia Bell Labs
Thursday Nov 1, 2018 09:06 - 10:09
Using compression codes for efficient data acquisition
Rayan Saab, University of California San Diego
Thursday Nov 1, 2018 10:31 - 11:09
New and Improved Binary Embeddings of Data (and Quantization for Compressed Sensing with Structured Random Matrices)
Laurent Jacques, University of Louvain
Thursday Nov 1, 2018 11:10 - 11:50
Dithered quantized compressive sensing with arbitrary RIP matrices
Waheed Bajwa, Rutgers University
Thursday Nov 1, 2018 13:34 - 14:41
Sample complexity bounds for dictionary learning from vector- and tensor-valued data
Maxim Goukhshtein, University of Toronto
Thursday Nov 1, 2018 14:42 - 15:13
Distributed Coding of Compressively Sensed Sources
Vincent Schellekens, Université Catholique de Louvain
Thursday Nov 1, 2018 15:44 - 16:11
Compressive Learning with quantized embedding of datasets
Xiugang Wu, University of Delaware
Thursday Nov 1, 2018 16:13 - 16:53
Minimax Learning for Remote Prediction
