Professor Tsachy Weissman

• Research Interests
• Students
• Other Collaborators
• Recent Work
• Recent Talks

Tutorials

• Recent Trends in Denoising

Workshops

• Entropy of Hidden Markov Processes and Connections to Dynamical Systems

Research Interests

• Information Theory
• Statistical Signal Processing
• Delay-Constrained and Complexity-Constrained Information Theory
• Denoising, Filtering and Prediction

Students    

Other Collaborators

• Amir Dembo
• Abbas El Gamal
• Vivek Farias
• Andrea Goldsmith
• Young-Han Kim
• Amos Lapidoth
• Shie Mannor
• Nuno Martins
• Neri Merhav
• Ciamac Moallemi
• Chandra Nair
• Erik Ordentlich
• Gadiel Seroussi
• Anelia Somekh-Baruch
• Ben Van Roy
• Sergio Verdu
• Krishnamurthy Viswanathan
• Marcelo Weinberger

Sample of Recent Work

 Communication with Feedback

• H. Permuter, T. Weissman, A. Goldsmith, "Finite state channels with time-invariant deterministic feedback," submitted.

• H. Permuter, P. Cuff, B. Van Roy, T. Weissman, "Capacity of the Trapdoor Channel with Feedback," submitted.

• N.C. Martins and T. Weissman, “Coding Schemes for Additive White Noise Channels with Feedback Corrupted by Quantization or Bounded Noise'', submitted.

• Y. H. Kim, A. Lapidoth and T. Weissman,  “On Error Exponents for Channels with Noisy Feedback”, Proc. 44th Annual Allerton Conf. on Communication, Control, and Computing,  Monticello, IL, September 27 -- 29th, 2006.

 Sequential Decision Making

• T. Weissman and N. Merhav, "Universal prediction of binary individual sequences in the presence of noise," IEEE Trans. Inform. Theory, vol. IT-47, no. 6, pp. 2151-2173, September 2001.

• N. Merhav and T. Weissman, "Scanning and prediction in multi-dimensional data arrays,"  IEEE Trans. Inform. Theory, vol. IT-49, no. 1, pp. 65-82, January 2003.

• T. Weissman and N. Merhav, "On Competitive Predictability and its Relation to Rate-Distortion theory'' IEEE Trans. Inform. Theory, vol. 49, no. 12, pp. 3185-3194, December 2003.

• T. Weissman and N. Merhav, "Universal prediction of random binary sequences in a noisy environment,'' Annals of Applied Probability, vol. 14, no. 1, pp. 54-89, February 2004.

• V. F. Farias, C.C. Moallemi, B. Van Roy and T. Weissman, "A Universal Scheme for Learning," Int. Symp. Inf. Th. , Adelaide, Australia, September 2005.

• T. Weissman, E. Ordentlich, M. Weinberger, A. Somekh-Baruch, N. Merhav, "Universal Filtering via Prediction," submitted.

• T. Moon and T. Weissman, "Universal Filtering via Hidden Markov Modeling", submitted.

• A. Cohen, N. Merhav and T. Weissman, "Universal scanning and sequential decision making for multidimensional data," Int. Symp. Inf. Th., Seattle, Washington, July 2006.

• T. Weissman, ”How to filter an ‘individual sequence with feedback’,” submitted.

Lossless and Lossy Source Coding

• T. Weissman and N. Merhav, "Tradeoffs between the excess-code-length exponent and the excess-distortion exponent in lossy source coding," IEEE Trans. Inform. Theory, vol. IT-48, no. 2, pp. 396-415, February 2002.

• T. Weissman and N. Merhav, "On limited-delay lossy coding and filtering of individual sequences," IEEE Trans. Inform. Theory, vol. IT-48, no. 3, pp. 721-733, March 2002.

• A. Dembo and T. Weissman, "The Minimax Distortion Redundancy in Noisy Source Coding," IEEE Trans. Inform. Theory, vol. IT-49, pp. 3020-3030, November 2003.

• T. Weissman, "Universally Attainable Error-Exponents for Rate-Distortion Coding of Noisy Sources", IEEE Trans. Inform. Theory, vol. 50, no. 6, pp. 1229-1246, June 2004.

• T. Weissman and E. Ordentlich, "The empirical distribution of rate-constrained codes", IEEE Trans. Inform. Theory, vol. 51, no. 11, pp. 3718-3733, Nov. 2005.

• T. Weissman and N. Merhav, "On Causal Source Codes with Side Information,'' IEEE Trans. Inform. Theory, vol. 51, no. 11, pp. 4003-4013, Nov. 2005.

• T. Weissman, "Not all universal source codes are pointwise universal", unpublished.

• T. Weissman and A. El Gamal, "Source Coding with Limited Side Information Lookahead at the Decoder", to appear in IEEE Trans. Inform. Theory.

Joint Source-Channel Coding

• E. Ordentlich, G. Seroussi, S. Verdu, K. Viswanathan, M. Weinberger and T. Weissman, "Channel Decoding of Systematically Encoded Unknown Redundant Sources," Int. Symp. Inf. Th. , p. 165, Chicago, IL, June-July 2004.

• S. Matloub and T. Weissman, "Universal zero-delay joint source-channel coding", to appear in IEEE Trans. Inform. Theory.

 Denoising

• E. Ordentlich, G. Seroussi, S. Verdu, M. Weinberger and T. Weissman, "A universal discrete image denoiser and its application to binary images", Proc. IEEE Int. Conf. on Image Processing, p. 117-120, vol. 1, Barcelona, Catalonia, Spain, September 2003.

• E. Ordentlich, M. Weinberger and T. Weissman, "Efficient Pruning of Bi-Directional Context Trees with Applications to Universal Denoising and Compression", 2004 IEEE Inf. Th. workshop, San Antonio, Texas, October 24-29, 2004.

• T. Weissman, E. Ordentlich, G. Seroussi, S. Verdu and M. Weinberger, "Universal Discrete Denoising: Known Channel", IEEE Trans. Inform. Theory, vol. 51, no. 1, pp. 5-28, January 2005.

• A. Dembo and T. Weissman, "Universal Denoising for the Finite-Input-General-Output Channel'', IEEE Trans. Inform. Theory, vol. 51, no. 4, pp. 1507-1517, April 2005.

• E. Ordentlich and M. Weinberger and T. Weissman, "Multi-Directional Context Sets with Applications to Universal Denoising and Compression," Int. Symp. Inf. Th. , Adelaide, Australia, September 2005.

• R. Zhang and T. Weissman, "Discrete Denoising for Channels with Memory", Communications in Information and Systems (CIS), vol. 5, no. 2, pp. 257-288, 2005.

• E. Ordentlich and T. Weissman, "On the optimality of symbol-by-symbol filtering and denoising'', IEEE Trans. Inform. Theory, vol. 52, no. 1, pp. 19-40, Jan. 2006.

• G. Gemelos, S. Sigurjonsson and T. Weissman, "Algorithms for Discrete Denoising Under Channel Uncertainty'', IEEE Trans. Signal Processing, vol. 54, no. 6, pp. 2263-2276, June 2006.

• G. Gemelos, S. Sigurjonsson and T. Weissman, "Universal Minimax Discrete Denoising under Channel Uncertainty'', to appear in IEEE Trans. Inform. Theory.

• S. Pereira and T. Weissman, "Denoising and Filtering Under Probability of Excess Loss Criterion.", To appear in…..

• K. Sivaramakrishnan and T. Weissman, "Universal Denoising of Discrete-time Continuous-Amplitude Signals", submitted.

• T. Moon and T. Weissman, "Discrete denoising with shifts", submitted.

Entropy

• E. Ordentlich and T. Weissman, "Asymptotics for the entropy rate of a hidden Markov process", 2004 IEEE Inf. Th. workshop, San Antonio, Texas, October 24-29, 2004.

• E. Ordentlich and T. Weissman, "Approximations for the Entropy Rate of a Hidden Markov Process," Int. Symp. Inf. Th. , Adelaide, Australia, September 2005.

• C. Nair, E. Ordentlich and T. Weissman, "On asymptotic filtering and entropy rate for a hidden Markov process in the rare transitions regime," Int. Symp. Inf. Th., Adelaide, Australia, September 2005.

• T. Weissman and S. Verdu, "Erasure Entropy," Int. Symp. Inf. Th., Seattle, Washington, July 2006.

• G. Gemelos and T. Weissman, "On the Entropy Rate of Pattern Processes", to appear in IEEE Trans. Inform. Theory.

Recent Talks

• "On optimal filtering and entropy rate of a hidden Markov process ", Berkeley EECS dept.

• "Discrete Universal Filtering (Through Incremental Parsing)", Princeton EE dept. and Wharton school Statistics dept.

• "Universal Minimax Discrete Denoising under Channel Uncertainty", UCSD EECS dept.

• "New Bounds on the Entropy Rate of Hidden Markov Processes", ISL Colloquium, Stanford University.

• "Discrete Denoising for Channels with Memory", Stanford Statistics Seminar

• "On Coding with Feedback in presence of Side Information", Bay Area Signals, Information, and Control Symposium

• "Source Coding with Limited Side Information Lookahead at the Decoder", Princeton EE Dept. & at the Advanced Network Colloquium Series, University of Maryland

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