Talks
2009
Harnessing Extreme Value Theory to an Information Theoretic Problem
Iterative Schemes for Discrete Lossy Compression
Mutual Information, Relative Entropy, and the Relationship Between Causal and NonCausal Mismatched Estimation in AWGN Channels
Iterative Schemes for Lossy Compression of an Unknown Source
Where is the Action in Information Theory?
2008
Rate Distortion via Markov Chain Monte Carlo
RateDistortion, Noise Removal, and MCMC
How to Clean Up Discrete Data
Discrete to Analog and Back: The DUDE Framework for Denoising Discrete and Analog Data
Lossy Compression via Markov Chain Monte Carlo
2007
The DUDE framework for continuous tone image denoising
Discrete Denoising with Shifts
An Information Theorist Cleans Up Discrete Data
Overview on entropy rate of hidden Markov processes
Cleaning Up Discrete Data: An Information Theoretic Approach
The DUDE framework for Discrete Denoising and (some of) its applications
2006
The Role of Noisy Feedback in Communication
Robustness and Sensitivity of the SchalkwijkKailath Scheme
2005
Source Coding with Limited Side Information Lookahead at the Decoder
On Coding with Feedback in the Presence of Side Information
Discrete Denoising for Channels with Memory
New bounds on the entropy rate of hidden Markov processes
2004
Asymptotics for the entropy rate of a hidden Markov process
Universal Minimax Discrete Denoising under Channel Uncertainty
Discrete Universal Filtering Through Incremental Parsing
2003
On optimal filtering and entropy rate of a hidden Markov process
ContextBased Denoising: Universally Optimal, Practical Schemes
On the Optimality of Symbol by Symbol Filtering and Denoising
2002
DUDE: A New Approach for Recovering NoiseCorrupted Data
Universal Discrete Denoising: Known Channel
On Causal Source Codes with Side Information
2001
Scanning and Prediction in MultiDimensional Data Arrays
Universal Schemes for Attaining the FiniteState Predictability in the Presence of Noise
2000
On Universal Compression of MultiDimensional Data Arrays Using SelfSimilar Curves
Twofold Universal Prediction Schemes for Noisy Data
1999
Prediction Relative to a Set of Experts in the Presence of Noise
