Ananda Theertha Suresh Google Research, New York email: theertha at google dot com [Google scholar]

About me

I am a senior research scientist at Google Research, New York. I obtained my PhD in electrical and computer engineering from University of California, San Diego, where I was advised by Alon Orlitsky. Prior to joining UCSD, I obtained Bachelors degree in Engineering Physics from Indian Institute of Technology, Madras.

Research

''What is unseen, is not necessarily unknown'' - Wendelessen

I am interested in machine learning, information theory, and statistics. I have worked on problems related to distribution learning, property testing, and universal compression over large domains. Recently, I am interested in understanding the effects of memory and communication on optimization and learning.

Publications

By year     By topic     Journal articles

• Model-powered conditional independence test, NIPS 2017
  with R. Sen, K. Shanmugam, A. Dimakis, and S. Shakkottai [pdf]

• Multiscale quantization for fast similarity search, NIPS 2017
  with X. Wu, R. Guo, D. Holtmann-Rice, D. Simcha, F. Yu, and S. Kumar [pdf]

• Lattice rescoring strategies for long short term memory language models in speech recognition, ASRU 2017
  with S. Kumar, M. Nirschl, D. Holtmann-Rice, H. Liao, and F. Yu [pdf]

• Distributed mean estimation with limited communication, ICML 2017
  with F. Yu, H. B. McMahan, and S. Kumar [pdf]

• A unified maximum likelihood approach for optimal distribution property estimation, ICML 2017
  with J. Acharya, H. Das, and A. Orlitsky [pdf]

• Maximum selection and ranking under noisy comparisions, ICML 2017
  with M. Falahatgar, A. Orlitsky, and V. Pichapati [pdf]

• Sample complexity of population recovery, COLT 2017
  with Y. Polyanskiy and Y. Wu [pdf]

• Orthogonal random features, NIPS 2016
  with F. Yu, K. Choromanski, D. Holtmann-Rice, and S. Kumar [pdf] (Oral presentation)

• Federated learning: Strategies for improving communication efficiency, NIPS PMPML workshop 2016
  with J. Konecny, H. B. McMahan, F. X. Yu, P. Richtarik, and D. Bacon [pdf]

• Optimal prediction of the number of unseen species, PNAS 2016
  with A. Orlitsky and Y. Wu [pdf]

• Learning Markov distributions: Does estimation trump compression?, ISIT 2016
  with M. Falahatgar, A. Orlitsky, and V. Pichapati [pdf]

• Estimating the number of defectives with group testing, ISIT 2016
  with M. Falahatgar, A. Jafarpour, A. Orlitsky, and V. Pichapati [pdf]

• Competitive distribution estimation: Why is Good-Turing good, NIPS 2015
  with A. Orlitsky [pdf] [talk] (Best Paper Award)

• Faster algorithms for testing under conditional sampling, COLT 2015
  with M. Falahatgar, A. Jafarpour, A. Orlitsky, and V. Pichapati [jmlr]

• On learning distributions from their samples, COLT 2015
  with S. Kamath, A. Orlitsky, and V. Pichapati [jmlr]

• Automata and graph compression, ISIT 2015
  with M. Mohri and M. Riley [pdf] [implementation]

• Universal compression of power-law distributions, ISIT 2015
  with M. Falahatgar, A. Jafarpour, A. Orlitsky, and V. Pichapati [pdf]

• Sparse solutions to nonnegative linear systems and applications, AISTATS 2015
  with A. Bhaskara and M. Zaghimoghaddam [arXiv]

• The complexity of estimating Renyi entropy, SODA 2015
  with J. Acharya, A. Orlitsky and H. Tyagi [arXiv]

• Near-optimal-sample estimators for spherical Gaussian mixtures, NIPS 2014
  with J. Acharya, A. Jafarpour, and A. Orlitsky [arXiv] [talk at simons]

• Sorting with adversarial comparators and application to density estimation, ISIT 2014
  with J. Acharya, A. Jafarpour, and A. Orlitsky [pdf]

• Efficient compression of monotone and m-modal distributions, ISIT 2014
  with J. Acharya, A. Jafarpour, and A. Orlitsky [pdf]

• Poissonization and universal compression of envelope classes, ISIT 2014
  with J. Acharya, A. Jafarpour, and A. Orlitsky [pdf]

• Sublinear algorithms for outlier detection and generalized closeness testing, ISIT 2014
  with J. Acharya, A. Jafarpour, and A. Orlitsky [pdf]

• Optimal probability estimation with applications to prediction and classification, COLT 2013
  with J. Acharya, A. Jafarpour, and A. Orlitsky [pdf] [talk]

• Tight Bounds for Universal Compression of Large Alphabets, ISIT 2013
  with J. Acharya, H. Das, A. Jafarpour, and A. Orlitsky [pdf]

• A competitive test for uniformity of monotone distributions, AISTATS 2013
  with J. Acharya, A. Jafarpour, and A. Orlitsky [pdf]

• Competitive classification and closeness testing, COLT 2012
  with J. Acharya, H. Das, A. Jafarpour, A. Orlitsky, and S. Pan [pdf] [talk]

• On the query computation and verification of functions, ISIT 2012
  with H. Das, A. Jafarpour, A. Orlitsky, and S. Pan [pdf]

• Strong and weak secrecy in wiretap channels, invited paper at ISTC 2010
  A. Subramanian, A. T. Suresh, S. Raj, A. Thangaraj, M. Bloch, and S. W. McLaughlin [pdf]

• Strong secrecy for erasure wiretap channels, ITW 2010
  A. T. Suresh, A. Subramanian, A. Thangaraj, M. Bloch, and S. W. McLaughlin [pdf]

• On optimal timer-based distributed selection For rate-adaptive multi-user diversity systems, NCC 2010
  A. T. Suresh, N. B. Mehta, and V. Shah [pdf] (Best Paper Award in Communications track)