Publications

Preprints

  1. (with Z. Goldfeld, K. Greenewald, and Y. Polyanskiy) “Convergence of smoothed empirical measures with applications to entropy estimation.” Submitted, 2019. arXiv
  2. (with G. Mena) “Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem.” Submitted, 2019. arXiv
  3. “Sharper rates for estimating differential entropy under Gaussian convolutions.” Technical report, 2018. PDF
  4. (with J. Altschuler, F. Bach, and A. Rudi) “Massively scalable Sinkhorn distances via the Nyström method.” Submitted, 2018. arXiv, preliminary technical report
  5. (with A. S. Bandeira, B. Blum-Smith, J. Kileel, A. Perry, and A. S. Wein) “Estimation under group actions: recovering orbits from invariants.” Submitted, 2018. arXiv
  6. (with A. S. Bandeira & P. Rigollet) “Optimal rates of estimation for multi-reference alignment.” Submitted, 2017. arXiv

Conference papers

  1. (with Q. Berthet) “Estimation of smooth densities in Wasserstein distance.” Proceedings of the 32nd Conference On Learning Theory (COLT 2019), to appear. arXiv
  2. (with Z. Goldfeld, K. Greenewald, and Y. Polyanskiy) “Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions.” International Symposium on Information Theory (ISIT 2019), to appear.
  3. (with A Forrow, J. Hütter, M. Nitzan, P. Rigollet, and G. Schiebinger) “Statistical optimal transport via factored couplings.” 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), to appear. arXiv
  4. “An explicit analysis of the entropic penalty in linear programming.” Proceedings of the 31st Conference On Learning Theory (COLT 2018). PDF, video of presentation
  5. (with C. Mao and P. Rigollet) “Minimax rates and efficient algorithms for noisy sorting.” Algorithmic Learning Theory (ALT 2018). PDF
  6. (with J. Altschuler & P. Rigollet) “Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration.” Advances in Neural Information Processing Systems 30 (NeurIPS 2017), selected for spotlight presentation. PDF
  7. (with V. Perchet & P. Rigollet) “Online learning in repeated auctions.” Proceedings of the 29th Annual Conference on Learning Theory (COLT 2016). PDF, video of presentation

Journal articles

  1. (with A. Perry, A. S. Bandeira, P. Rigollet, and A. Singer) “The sample complexity of multi-reference alignment.” In SIAM Journal on Mathematics of Data Science, to appear. arXiv
  2. (with P. Rigollet) “Uncoupled isotonic regression via minimum Wasserstein deconvolution.” In Information and Inference: A Journal of the IMA, to appear. arXiv, video of related talk
  3. (with P. Rigollet) “Entropic optimal transport is maximum-likelihood deconvolution.” In Comptes Rendus Mathématique, 356(11-12), 2018. PDF
  4. (with F. Bach) “Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance.” In Bernoulli, to appear. PDF
  5. (with S. Klassen and D. Evans) “Semi-supervised machine learning approaches for predicting the chronology of archaeological sites: A case study of temples from medieval Angkor, Cambodia.” In PLOS One. 13(11), 2018. PDF
  6. “Approximately certifying the restricted isometry property is hard.” In IEEE Transactions on Information Theory. 64(8), 2018. arXiv
  7. (with M. Sawhney) “Further results on arc and bar k-visibility graphs.” In Minnesota Journal of Undergraduate Mathematics. 3(1), 2018. (Project mentored through MIT PRIMES.) PDF
  8. (with S. Billey) Appendix to “Permutations with Kazhdan-Lusztig polynomial P_{id,w}(q) = 1 + q^h” by Alexander Woo. In Electronic Journal of Combinatorics. 16(2), 2009. PDF

Refereed book chapters

  1. “Multinational War is Hard.” In Jennifer Beineke and Jason Rosenhouse, editors, The Mathematics of Various Entertaining Subjects, Volume 2. Princeton, 2017. PDF