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Research Interests Information Theory Statistical Signal Processing Delay-Constrained and Complexity-Constrained Information Theory Denoising, Filtering and Prediction Tutorials Workshops
Recent Sponsored Projects [link] Some new lossy compression algorithms [link]
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~Shannon Theory T. Weissman, "The Relationship between Causal and Non-Causal Mismatched Estimation in Continuous-Time AWGN Channels," Submitted. ~Lossy Compression and Rate-Distortion Theory ~Communication, Channel Capacity, and Feedback |
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Current: Former: Asaf Cohen (Postdoctoral fellow at Caltech)
George Gemelos (Director
- Proprietary Trading, Styrmir Sigurjonsson (Portfolio Management - Straumur Investment Bank)
Kamakshi Sivaramakrishnan
(Postdoctoral fellow - Rui Zhang (Assistant Professor - Institute for Infocomm Research (I²R)) |
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Lossy Compression and Rate-Distortion Theory
T. Weissman and N. Merhav, “On Causal Source Codes with Side Information”, IEEE Trans. Inform. Theory, vol. 51, no. 11, pp. 4003-4013, November 2005.
T. Weissman and E. Ordentlich, “The empirical distribution of rate-constrained codes”, IEEE Trans. Inform. Theory, vol. 51, no. 11, pp. 3718-3733, November 2005.
N. Merhav and T. Weissman, “Coding for the feedback Gel’fand-Pinsker channel and the feedforward Wyner-Ziv source”, IEEE Trans. Inform. Theory, vol. 52, no. 9, pp. 4207 - 4211, September 2006.
T. Weissman and A. El Gamal, “Source Coding with Limited Side Information Look ahead at the Decoder”, IEEE Trans. Inform. Theory, vol. 52, no. 12, pp. 5218 - 5239, December 2006.
S. Matloub and T. Weissman, “Universal Zero-Delay Joint Source-Channel Coding”, IEEE Trans. Inform. Theory, vol. 52, no. 12, pp. 5240 - 5250, December 2006.
S. Verdú and T. Weissman, “The Information Lost in Erasures,” accepted to IEEE Trans. Inform. Theory.
S. Jalali, S. Verdú and T. Weissman, “A Universal Wyner-Ziv Scheme for Discrete Sources,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
S. Jalali and T. Weissman, “New Bounds on the Rate-Distortion Function of a Binary Markov Source,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
S. Jalali and T. Weissman, “Lossy Source Coding via Markov Chain Monte Carlo,” Proc. 2008 International Zurich Seminar on Communications, p. 80–83, Zurich, Switzerland, March 12–14, 2008.
S. Bross and T. Weissman, “On successive refinement for the Wyner-Ziv problem with partially cooperating decoders,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
A. Gupta, S. Verdú and T. Weissman, “Linear-Time Near-Optimal Lossy Compression,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
S. Jalali and T. Weissman, “Rate Distortion Coding of Discrete Sources via Markov Chain Monte Carlo,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
S. Jalali, A. Montanari, T. Weissman, "An implementable scheme for universal lossy compression of discrete Markov sources," accepted, DCC 2009.
· T. Weissman, E. Ordentlich, G. Seroussi, S. Verdú 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.
· R. Zhang and T. Weissman, “Discrete Denoising for Channels with Memory”, Comm. in Information and Systems, vol. 5, no. 2, pp. 257-288, 2005.
· T. Weissman and E. Ordentlich, “The empirical distribution of rate-constrained codes”, IEEE Trans. Inform. Theory, vol. 51, no. 11, pp. 3718-3733, November 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, January 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”, IEEE Trans. Inform. Theory, vol. 52, no. 8, pp. 3476-3497, August 2006.
· S. Pereira and T. Weissman, “Denoising and filtering under the probability of excess loss criterion”, IEEE Trans. Inform. Theory, vol. 53, no. 4, pp. 1265 - 1281, April 2007.
· T. Weissman, E. Ordentlich, M. Weinberger, A. Somekh-Baruch and N. Merhav, “Universal Filtering via Prediction”, IEEE Trans. Inform. Theory, vol. 53, no. 4, pp. 1253 - 1264, April 2007.
· E. Ordentlich, G. Seroussi, S. Verdú, M. Weinberger and T. Weissman, “Reflections on the DUDE”, IEEE Information Theory Society Newsletter, vol. 57, no. 2, pp. 5-10, June 2007 (invited).
· T. Moon and T. Weissman, “Discrete Universal Filtering via Hidden Markov Modelling”, IEEE Trans. Inform. Theory, vol. 54, no. 2, pp. 692 – 708, February 2008.
· T. Weissman, “How to filter an ‘individual sequence with feedback’,” IEEE Trans. Inform. Theory, vol. 54, no. 8, pp. 3831–3841, August 2008.
· K. Sivaramakrishnan and T. Weissman, “Universal denoising of discrete time continuous-amplitude signals,” accepted to IEEE Trans. Inform. Theory.
· A. Cohen, T. Weissman and N. Merhav, “Scanning and sequential decision making for multi-dimensional data, Part II: the noisy case,” accepted to IEEE Trans. Inform. Theory.
· S. Verdú and T. Weissman, “The Information Lost in Erasures,” accepted to IEEE Trans. Inform. Theory.
· E. Ordentlich, M. Weinberger and T. Weissman, “Multi-Directional Context Sets with Applications to Universal Denoising and Compression,” Proc. Int. Symp. Inf. Th., p. 1270-1274, Adelaide, Australia, September 2005.
· K. Sivaramakrishnan and T. Weissman, “Universal denoising of continuous valued signals with applications to images,” Proc. Int. Conf. Image Proc., Atlanta, Georgia, October 2006.
· S. Jalali, S. Verdú and T. Weissman, “A Universal Wyner-Ziv Scheme for Discrete Sources,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
· K. Sivaramakrishnan and T. Weissman, “A Context Quantization Approach to Universal Denoising,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
· T. Moon and T. Weissman, “Competitive On-line Linear FIR MMSE Filtering,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
· A. Cohen, N. Merhav and T. Weissman, “Scanning, Filtering, and Prediction for Random Fields Corrupted by Gaussian Noise,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
· T. Moon and T. Weissman, “Discrete Denoising with Shifts,” Proc. 45th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, September 26 – 28th, 2007 (invited).
· S. Jalali and T. Weissman, “Near Optimal Lossy Source Coding and Compression-Based Denoising via Markov Chain Monte Carlo,” Proc. 42nd Annu. Conf. on Information Sciences and Systems (CISS 2008), Princeton, NJ, March 19 – 21, 2008 (invited).
Communication, Channel Capacity, and Feedback
N. Merhav and T. Weissman, “Coding for the feedback Gel’fand-Pinsker channel and the feedforward Wyner-Ziv source”, IEEE Trans. Inform. Theory, vol. 52, no. 9, pp. 4207 - 4211, September 2006.
H. Permuter, P. Cuff, B. Van Roy and T. Weissman, “Capacity of the Trapdoor Channel with Feedback,” IEEE Trans. Inform. Theory, vol. 54, no. 7, pp. 3150–3165, July 2008.
T. Weissman, “How to filter an ‘individual sequence with feedback’,” IEEE Trans. Inform. Theory, vol. 54, no. 8, pp. 3831–3841, August 2008.
N. C. Martins and T. Weissman, “Coding Schemes for Additive White Noise Channels with Feedback Corrupted by Quantization or Bounded Noise”, to appear in IEEE Trans. Inform. Theory, September 2008.
Y. H. Kim, A. Lapidoth and T. Weissman, “On Error Exponents for Channels with Noisy Feedback”, Proc. 44th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, September 27 – 29th, 2006 (invited).
Y. H. Kim, A. Lapidoth and T. Weissman, “Upper Bounds on Error Exponents of Channels with Feedback”, Proc. 24th IEEE Conf. Electrical and Electronics Engineers Eilat, Israel, November 15 – 17th, 2006 (invited).
Y.-H. Kim, A. Lapidoth and T. Weissman, “The Gaussian Channel with Noisy Feedback,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
H. Permuter, P. W. Cuff, B. Van Roy and T. Weissman, “Capacity and Zero-Error Capacity of the Chemical Channel with Feedback,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
H. Permuter and T. Weissman, “On Separation in the Presence of Feedback,” Proc. 2007 IEEE Inf. Th. Workshop (ITW2007), Lake Tahoe, California, September 2-6, 2007 (invited).
H. Permuter, T. Weissman and J. Chen, “On the Capacity of Finite- State Channels,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
H. Permuter and T. Weissman, “New Bounds for the Capacity Region of the Finite-State Multiple Access Channel,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
H. Permuter, Y. H. Kim and T. Weissman, “On Directed Information and Gambling,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
T. Weissman, "Capacity of Channels with Action-Dependent States," submitted.
· 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, January 2006.
· S. Matloub and T. Weissman, “Universal Zero-Delay Joint Source-Channel Coding”, IEEE Trans. Inform. Theory, vol. 52, no. 12, pp. 5240 - 5250, December 2006.
· S. Pereira and T. Weissman, “Denoising and filtering under the probability of excess loss criterion”, IEEE Trans. Inform. Theory, vol. 53, no. 4, pp. 1265 - 1281, April 2007.
· • T. Weissman, E. Ordentlich, M. Weinberger, A. Somekh-Baruch and N. Merhav, “Universal Filtering via Prediction”, IEEE Trans. Inform. Theory, vol. 53, no. 4, pp. 1253 - 1264, April 2007.
· A. Cohen, N. Merhav and T. Weissman, “Scanning and sequential decision making for multi-dimensional data, Part I: the noiseless case”, IEEE Trans. Inform. Theory, vol. 53, no. 9, pp. 3001 - 3020, September 2007.
· T. Moon and T. Weissman, “Discrete Universal Filtering via Hidden Markov Modelling”, IEEE Trans. Inform. Theory, vol. 54, no. 2, pp. 692 – 708, February 2008.
· T. Weissman, “How to filter an ‘individual sequence with feedback’,” IEEE Trans. Inform. Theory, vol. 54, no. 8, pp. 3831–3841, August 2008.
· A. Cohen, T. Weissman and N. Merhav, “Scanning and sequential decision making for multi-dimensional data, Part II: the noisy case,” accepted to IEEE Trans. Inform. Theory.
· V. F. Farias, C. C. Moallemi, B. Van Roy and T. Weissman, “A Universal Scheme for Learning,” Proc. Int. Symp. Inf. Th., p. 1158–1162, Adelaide, Australia, September 2005.
· T. Moon and T. Weissman, “Competitive On-line Linear FIR MMSE Filtering,” Proc. Int. Symp. Information Theory, Nice, France, July 2007.
· H. Permuter, Y. H. Kim and T. Weissman, “On Directed Information and Gambling,” Proc. Int. Symp. Information Theory, Toronto, Ontario, Canada, July 2008.
· 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, January 2006.
· G. Gemelos and T. Weissman, “On the Entropy Rate of Pattern Processes”, IEEE Trans. Inform. Theory, vol. 52, no. 9, pp. 3994 - 4007, September 2006.
· S. Verdú and T. Weissman, “The Information Lost in Erasures,” accepted to IEEE Trans. Inform. Theory.
· E. Ordentlich and T. Weissman, “Approximations for the Entropy Rate of a Hidden Markov Process,” Proc. Int. Symp. Inf. Th., p. 2198–2202, 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,” Proc. Int. Symp. Inf. Th., p. 1838–1842, Adelaide, Australia, September 2005.
* "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
