(Previous years’ talks can be found here.)
24-Mar Yanjun Han MIT
Two Recent Lower Bounds for Interactive Decision Making
12-May Alexandra Gallyas-Sanhueza Cornell University
Sparsity-Exploiting Adaptive Denoising of Channel Estimates for Multi-Antenna Wireless Communication Systems
26-May Flavio du Pin Calmon Harvard School of Engineering and Applied Sciences
Facets of Fair Machine Learning
06-Oct Jouni Sirén and Benedict Paten UC Santa Cruz
GBZ File Format for Pangenome Graphs
27-Oct Julia Salzman Stanford
SPLASH: Statistically Primary aLignment Agnostic Sequence Hashing
03-Nov Yibo Yang UC Irvine
Rate-distortion estimation through statistical learning and optimal transport
10-Nov Hyeji Kim University of Texas at Austin
Neural Distributed Source Coding
17-Nov Shirin Saeedi Bidokhti University of Pennsylvania
Learning-Based Data Compression: Fundamental limits and Algorithms
08-Dec Ashok Vardhan Makkuva École Polytechnique Fédérale de Lausanne (EPFL)
LASER: Linear Compression in Wireless Distributed Optimization
19-Jan Hyunjik Kim and Jonathan Schwarz Google
Data Compression with Neural Fields
26-Jan Debargha Mukherjee Google
Towards a next generation video codec from the Alliance for open Media
09-Feb Taesup Moon (문태섭) Seoul National University
Refined Data Sampling and Re-weighting for Efficient and Fair Learning
16-Feb Cheuk Ting Li Chinese University of Hong Kong
Undecidable Problems in Information Theory
12-Apr Amichai Painsky Tel Aviv University
Large Alphabet Inference
19-Apr Osama Hanna University of California, Los Angeles (UCLA)
Stochastic Contextual Bandits are Not Harder than Linear Bandits
25-Sep Meir Feder Tel-Aviv University
Addressing Large Models - Multiple and Hierarchical Universality
10-Oct Sandeep Pradhan University of Michigan
Quantum Bayesian Framework for Efficient Storage of Quantum Information
29-Oct Haewon Jeong University of California, Santa Barbara
From Model Collapse to Biased Teachers: Challenges in Responsible Generative AI
01-Nov Mohamed Seif Princeton University
Differentially Private Community Detection over Stochastic Block Models
06-Dec Ashok Makkuva École Polytechnique Fédérale de Lausanne
Attention with Markov: A Markovian Tale of Transformers
21-Feb Haim Permuter Ben Gurion University
Data-Driven Approach for Capacity Estimation, Polar codes, and Compression.
25-Apr Basil Saeed Stanford University"
Recent progress in high-dimensional asymptotics of empirical risk minimization
28-Mar Xiangxiang Xu MIT
Deep Learning From an Information Perspective
21-Jan Eren Kizildag MIT
Algorithmic Obstructions in the Random Number Partitioning Problem
04-Feb Dimitris Papailiopoulos University of Wisconsin-Madison
Learning by Pruning and the Hunt for Lottery Tickets
11-Feb Deepanshu Vasal Northwestern University
Sequential linear coding for multi user Gaussian channels with active noisy feedback
18-Feb Pramod Viswanath University of Illinois at Urbana-Champaign
KO Codes
25-Feb Ashish Khisti University of Toronto
Learned Data Compression
04-Mar Haizi Yu University of Chicago
Information Lattice Learning
11-Mar Deniz Gunduz Imperial College London
Semantic vs. Effective Communications
15-Apr David Hong University of Pennsylvania
Balanced group testing via hypergraph factorization for COVID-19
03-Jun Elad Romanov Stanford University
On the Role of Channel Capacity in Learning Gaussian Mixture Models
07-Oct Byron Knoll Google
Extreme Lossless Text Compression
14-Oct Dmitri Pavlichin Amazon
A Deep Dive into the Craft of Building Data Compressors
21-Oct Ilya Grebnov Microsoft
Burrows–Wheeler transform and Compression via Substring Enumeration (CSE)
28-Oct James Townsend University of Amsterdam
Latent Variables and Lossless Compression
04-Nov Jan Skoglund Google
Speech and Audio Compression in the Neural Era
11-Nov Eduardo Pavez University of Southern California
Graph-Based Compression of 3D Point Cloud Attributes
18-Nov George Toederici Google Research
VCT: A Video Compression Transformer
01-Dec Mattan Erez University of Texas at Austin
Every Bit Counts -- Compressed Main Memory Architectures
02-Dec Andrey Norkin Netflix
Video coding your next smartphone will actually use
12-Feb Ziv Goldfeld Cornell University
Scaling Wasserstein distances to high dimensions via smoothing
19-Feb Anastasios Angelopoulos UC Berkeley
Distribution-Free, Risk-Controlling Prediction Sets
21-May Ziv Scully Carnegie Mellon University
The Gittins Policy is Nearly Optimal in the M/G/k under Extremely General Conditions
28-May Oron Sabag Caltech
Feedback capacity of Gaussian channels with memory
29-Oct Alankrita Bhatt UC San Diego
Universal Probability and Its Applications
05-Nov Haim Permuter Ben-Gurion University
Estimating and optimizing Information Measures using neural networks and its application in communication
12-Nov Lydia Zakynthinou Northeastern University
Differentially Private Covariance-adaptive Mean Estimation
19-Nov Rashmi Vinayak Carnegie Mellon University
Convertible Codes: Enabling Redundancy Tuning in Large-scale Storage Systems
18-Sep Yanjun Han Stanford University
Learning to Bid in Repeated First-price Auctions
25-Sep Yanjun Han Stanford University
High-accuracy Optimality and Limitation of the Profile Maximum Likelihood
13-Nov David Woodruff CMU
A Very Sketchy Talk
