Email: jasonalt [at] mit [dot] edu
I am a fourth year PhD student at MIT. I am fortunate to be advised by Pablo Parrilo. My research is supported by an NSF GRFP grant.
Previously, I was an undergrad at Princeton (class of '16) under the wonderful supervision of Elad Hazan and Emmanuel Abbe. I spent 2 of my undergrad summers interning in tech (at Google/Google Research) and the other 2 summers interning on Wall Street (DE Shaw and Tower Research Capital).
In my free time, I like to play chess. I obtained an International Master norm in Spain in 2015.
Massively scalable Sinkhorn distances via the Nyström method
Jason Altschuler, Francis Bach, Alessandro Rudi, Jonathan Weed.
Conference on Neural Information Processing Systems (NeurIPS), 2019.
Best arm identification for contaminated bandits
Jason Altschuler, Victor-Emmanuel Brunel, Alan Malek.
Journal of Machine Learning Research (JMLR), 2019.
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
[pdf, poster, NeurIPS short video]
Jason Altschuler, Jonathan Weed, Philippe Rigollet.
Conference on Neural Information Processing Systems (NeurIPS), 2017. (Selected for Spotlight presentation)
Inclusion of forbidden minors in random representable matroids
Jason Altschuler, Elizabeth Yang.
Discrete Mathematics, 2017.
Greedy column subset selection: new bounds and distributed algorithms
[pdf, poster, slides]
Jason Altschuler, Aditya Bhaskara, Gang Fu, Vahab Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam.
International Conference on Machine Learning (ICML), 2016.
Rapid analysis and exploration of fluorescence microscopy images
Benjamin Pavie, Satwik Rajaram, Austin Ouyang, Jason Altschuler, Robert Steininger, Lani Wu, Steven Altschuler.
Journal of Visual Experiments (JoVE), 2014.
Approximation algorithms for Independent Set via semidefinite programming hierarchies and randomized rounding
Jason Altschuler, Matt Brennan.
Expository final project for David Karger's Randomized Algorithms course, 2017.
Minimax rates for online learning with limited decision changes (superseded by this paper in MOR/COLT)
Undergrad thesis for Princeton CS department, 2016. Advised by Elad Hazan.
Probabilistic linear Boolean classification
Undergrad thesis for Princeton math department, 2016. Advised by Emmanuel Abbe.