Information Theory Lab: Publications

Preprints

• V. Bagaria, A. Dembo, S. Kannan, S. Oh, D. Tse, P. Viswanath, X. Wang, O. Zeitouni.
  Proof-of-Stake Longest Chain Protocols: Security vs Predictability

• Y. Jiang, J. Konečný, K. Rush, S. Kannan
  Improving Federated Learning Personalization via Model Agnostic Meta Learning

• R Sen, K Shanmugam, H Asnani, A Rahimzamani, S Kannan.
  Mimic and Classify: A meta-algorithm for Conditional Independence Testing.

• S. Kannan, J. Hui, K. Mazooji, D. Tse, and L. Pachter
  Shannon: An Information- Optimal de Novo RNA-Seq Assembler

• S. Li, M. Yu, S. Avestimehr, S. Kannan, and P. Viswanath
  PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security in Blockchains Si- multaneously

• A. Rahimzamani and S. Kannan
  Potential Conditional Mutual Information

Publications

• Y. Mao, S. Deb, S. Bojja, S. Kannan, K. Srinivasan.
  Optimal Peer-to-peer Network Design for Blockchains
  to appear in Proc. ACM Symposium on Principles of Distributed Computing (PODC) Aug. 2020.

• S. Mao, S. Kannan, L. Pachter and D.Tse.
  RefShannon: a genome-guided transcriptome assembler using sparse flow decomposition
  to appear in PLOS One

• H. Kim, Y. Jiang, S. Kannan, S. Oh, and P. Viswanath.
  Feedback Codes via Deep Learning
  Journal of Selected Areas in Information Theory (JSAIT) April 2020.

• Y. Jiang, H. Kim, H. Asnani, S. Kannan, S. Oh, and P. Viswanath.
  LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks
  Journal of Selected Areas in Information Theory (JSAIT) April 2020.

• E. Lin, S. Mukherjee, and S. Kannan
  A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis
  BMC Bioinformatics, vol. 21, no. 1, 2020.

• A. Varadhan, S. Kannan, S. Oh and P. Viswanath.
  Learning in Gated Neural Networks.
  International Conference on Artificial Intelligence & Statistics (AISTATS) 2020

• M.Yu, S. Sahraei, S.~Li, S.~Avestimehr, S.~Kannan, and P.~Viswanath
  ``Coded Merkle Tree: Solving Data Availability Attacks in Blockchains''
  Financial Cryptography (FC) 2020.

• X. Qiu, A. Rahimzamani, L. Wang, Q. Mao, T. Durham, J. McFaline-Figueroa, L. Saunders, C. Trapnell, and S. Kannan
  Towards inferring causal gene regulatory networks from single cell expression measurements .
  Cell Systems 2020.

• V. Bagaria, S. Kannan, D. Tse, G. Fanti, and P. Viswanath
  Deconstructing the Blockchain to Approach Physical Limits
  ACM Conference on Computer and Communication Security (CCS) 2019
  Talk at Scaling Bitcoin, 2019.

• Y. Jiang, H. Kim, H. Asnani, S. Kannan, S. Oh, and P. Viswanath
  Turbo Autoencoder: Deep learning based channel code for point-to-point communication channels
  to appear, Neural Information Processing Systems (NeurIPS) 2019.

• S. Li, M. Yu, S. Avestimehr, S. Kannan, and P. Viswanath
  Brief Announcement: Coded State Machines .
  Principles of Distributed Computing (PODC) 2019

• S. Mukherjee, H. Asnani and S. Kannan
  CCMI : Classifier based Conditional Mutual Information Estimation .
  Uncertainty in Aritical Intelligence (UAI) 2019

• A. Varadhan, S. Kannan, S. Oh and P. Viswanath.
  Globally Consistent Algorithms for Mixture of Experts .
  International Conference on Machine Learning (ICML) 2019

• S. Mukherjee, E. Lin, H. Asnani and S. Kannan
  ClusterGAN: Latent Space Clustering in Generative Adversarial Networks
  AAAI Conference on Artificial Intelligence (AAAI) 2019

• H. Kim, Y. Jiang, S. Kannan, S. Oh, and P. Viswanath
  Discovering Feedback Codes via Deep Learning
  Proc. Neural Information Processing Systems (NeurIPS), Dec. 2018

• A. Rahimzamani, H. Asnani, P. Viswanath and S. Kannan
  Estimators for Multivariate Information Measures in General Probability Spaces
  Proc. Neural Information Processing Systems (NeurIPS), Dec. 2018.

• R. Sen, K. Shanmugam, H. Asnani, A. Rahimzamani, S. Kannan
  Conditional independence testing via deep learning with provable p-value control
  Proc. Allerton Conference Oct. 2018.

• S. Mukherjee, Y. Zhang, S. Kannan, and G. Seelig,
  Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge
  Bioinformatics 2018.

• W. Mao, S. Diggavi and S. Kannan,
  Information-theoretic bounds for nanopore sequencing
  IEEE Transactions on Information theory, Apr. 2018 .

• S. Mukherjee, Y. Zhang, J. Fan, G. Seelig and S. Kannan
  Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge
  Intelligent Systems for Molecular Biology (ISMB), June 2018

• H. Kim, Y. Jiang, S. Kannan, S. Oh and P. Viswanath
  Communication Algorithms via Deep Learning
  International Conference on Learning Representations (ICLR) Jan. 2018.

• W. Gao, S. Kannan, S. Oh, and P. Viswanath
  Estimating Mutual Information for Discrete-Continuous Mixtures
  Proceedings of The Neural Information Processing Conference (NeurIPS), Dec. 2017 (Spotlight)

• H. Kim, W. Gao, S. Kannan, S. Oh, and P. Viswanath
  Discovering Potential Influence via Hypercontractivity
  Proceedings of The Neural Information Processing Conference (NeurIPS), Dec. 2017

• A. Rahimzamani and S. Kannan
  Potential Conditional Mutual Information: Estimators and Properties
  Proceedings of Allerton Conference on Communication, Computing and Control, 2017

• W. Mao, S. Diggavi and S. Kannan
  Models and information-theoretic bounds for nanopore sequencing
  Proceedings of IEEE International Symposium on Information Theory (ISIT), 2017

• M. Chaisson, S. Mukherjee, S. Kannan and E. Eichler
  Resolving Multicopy Duplications de novo Using Polyploid Phasing
  21st Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2017

• S. Mao, S. Mohajer, K. Ramchandran, D. Tse, and S. Kannan
  abSNP: RNA-Seq SNP Calling in Repetitive Regions via Abundance Estimation
  17th ACM Workshop on Algorithms in Bioinformatics (WABI) 2017.

• H. Kim, W. Gao, S. Kannan, S. Oh, and P. Viswanath,
  Discovering Potential Influence via Hypercontractivity
  Entropy, Special Edition, Dec. 2017.

• W. Gao, S. Kannan, S. Oh, and P. Viswanath
  Conditional dependence via shannon capacity: Axioms, estimators and applications
  Proceedings of The 33rd International Conference on Machine Learning (ICML), 2016.

• H. Hosseini, S. Kannan, B. Zhang, and R. Poovendran
  Learning temporal dependence from time-series data with latent variables
  IEEE Data Science and Advanced Analytics Conference (DSAA), 2016.

• A. Rahimzamani and S. Kannan
  Network inference via directed information: The deterministic limit
  in Proceedings of Annual Allerton Conf., Monticello, IL, Sep. 2015.

• R. Kidambi and S. Kannan
  On Shannon Capacity and Causal estimation
  Proceedings of Annual Allerton Conf., Monticello, IL, Sep. 2015.

• C. Chekuri, S. Kamath, S. Kannan and P. Viswanath
  Delay-Constrained Unicast and the Triangle-Cast Problem
  IEEE International Symposium on Information Theory (ISIT), Hong Kong, June 2015.

• F. Farnia, M. Razaviyayn, S. Kannan and D. Tse
  Minimum HGR Correlation Principle: from Marginals to Joint Distribution
  IEEE International Symposium on Information Theory (ISIT), Hong Kong, June 2015.

• C. Chekuri, S. Kannan , A. Raja, and P. Viswanath,
  Multicommodity flows and cuts in polymatroidal networks
  Download PDF
  SIAM Journal on Computing 2015.

• S. Kannan and P. Viswanath,
  Capacity of multiple unicasts in wireless networks: A polymatroidal approach
  Download PDF
  IEEE Transactions on Information Theory, Oct. 2014.

• Q. Geng, S. Kannan , and P. Viswanath,
  Interactive Interference Alignment
  Download PDF
  Jour. Selected Areas in Commun. Theory, special issue on Full-Duplex Networks, Sep. 2014.

• S. Kamath, S. Kannan , and P. Viswanath,
  Network capacity under traffic symmetry
  Download PDF
  IEEE Trans. Inform. Theory, July 2014.

• S. Kannan , S. Mohajer, and D. Tse,
  Fundamental Limits and Optimal Algorithms for DNA Variant Calling at
  Annual Allerton Conference, Monticello, Sep. 2014 (invited talk).

• S. Kannan , D. Tse, and L. Pachter,
  Optimal Transcriptome Assembly: From Algorithms to Software at
  Information Theory and Applications Workshop, San Diego, Feb. 2014 (invited).

• S. Kannan , D. Tse, and L. Pachter,
  Optimal Algorithms for Transcriptome Assembly presented at
  Genome Informatics Conf., Cold Spring Harbor Labs, NY, Nov. 2013 (invited talk).

• S. Kannan , D. Tse, and L. Pachter,
  Fundamental Limits for RNA Transcriptome Assembly presented at
  Allerton Conf., Monticello, IL, Sep. 2013 (invited talk).

• S. Kannan , S. Birenjith, and P. V. Kumar,
  DMT of Parallel-Path and Layered Networks Under the Half-Duplex Constraint
  Download PDF
  IEEE Transactions on Information Theory, June 2013

• S. Kannan and P. Viswanath,
  Multi-session Function Computation in Undirected Graphs
  Download PDF
  Jour. Selected Areas in Commun. Theory, special issue on In-Network Function Computation, April 2013.

• S. Kannan , Q. Geng, and P. Viswanath,
  Interactive Interference Alignment
  Proc. IEEE International Symposium on Information Theory (ISIT), Istanbul, July 2013.

• S. Kannan and P. Viswanath,
  Multi-terminal Function Multicasting in Undirected Graphs
  Proc. IEEE International Symposium on Information Theory (ISIT), Istanbul, July 2013.

• S. Kannan and P. Viswanath,
  Approximate Capacity of Interference Networks: A Polymatroidal Approach
  Information Theory and Applications (ITA) Workshop, San Diego, CA, Feb. 2013.

• S. Kannan , A. Raja, and P. Viswanath,
  Approximately Optimal Wireless Broadcasting
  Download PDF
  IEEE Transactions on Information Theory, Dec. 2012.

• S. Kannan , S. Birenjith, and P. V. Kumar,
  DMT of Multihop Networks: End Points and Computational Tools
  Download PDF
  IEEE Transactions on Information Theory, Feb. 2012.

• S. Kamath, S. Kannan , and P. Viswanath,
  Wireless networks with symmetric demands
  Proc. IEEE International Symposium on Information Theory (ISIT), Boston, 2012.

• S. Kannan and P. Viswanath,
  Constant-factor approximation of sum rate in wireless networks: A polymatroidal approach
  Information Theory and Applications (ITA) Workshop, San Diego, CA, Feb. 2012.

• C. Chekuri, S. Kannan , A. Raja, and P. Viswanath,
  Multicommodity flows and cuts in polymatroidal networks
  Innovations in Theoretical Computer Science Conference, Boston, Jan. 2012.

• S. Kannan and P. Viswanath,
  Multiple unicast on fading wireless networks: A separation scheme is approximately optimal
  Proc. IEEE International Symposium on Information Theory (ISIT), St.Petersburg, Russia, July, 2011.

• S. Kannan , A. Raja, and P. Viswanath,
  Local Phy + Global Flows: A layering principle for wireless networks
  Proc. IEEE International Symposium on Information Theory, St.Petersburg, Russia, July, 2011.

• S. Kannan , A. Raja, and P. Viswanath,
  Approximately Optimal Broadcasting-cum-multicasting in Wireless Networks
  Proc. IEEE International Symposium on Information Theory, St.Petersburg, Russia, July, 2011.

• S. Kannan , A. Raja, and P. Viswanath,
  Approximately optimal broadcasting in Wireless Networks
  IEEE Signal Proc. and Commn. Conference, Bangalore, July 2010.

• S. Kannan , S. Birenjith, P. Vijay Kumar,
  DMT of Multi-hop Cooperative Networks: Full-Duplex Performance with Half-Duplex Networks (invited) at
  Proc. IEEE Information Theory Workshop, Cairo, Egypt, Jan. 10.

• S. Kannan , S. Birenjith, P. Vijay Kumar,
  Multi-hop Cooperative Wireless Networks: DM Tradeoff and Optimal Code Design (invited) at
  Proc. of ITA, San Diego, CA, Feb. 08.

• S. Kannan , S. Birenjith, P. Vijay Kumar,
  DMT of multi--hop cooperative networks--Part I: K--parallel--path--networks
  Proc. IEEE Intl. Symp. Info. Theory (ISIT), Toronto, July 08.

• S. Kannan , S. Birenjith, P. Vijay Kumar,
  DMT of multi--hop cooperative networks--Part II: Layered and multi--antenna networks
  Proc. IEEE Intl. Symp. Info. Theory (ISIT), Toronto, July 08.

• S. Kannan , S. Birenjith, P. Vijay Kumar,
  Diversity and degrees of freedom of cooperatives wireless networks
  Proc. IEEE Intl. Symp. Info. Theory (ISIT), Toronto, July 08.

• R.N. Krishna Kumar, N. Naveen, S. Kannan, and P. Vijay Kumar,
  Diversity multiplexing tradeoff of asynchronous cooperative relay networks (invited)
  Proc. Allerton Conf., Monticello, IL, Sep. 2008.