Email: jasonalt [at] mit [dot] edu
I am a second year PhD student at MIT. I am fortunate to be advised by Pablo Parrilo. My current research interests are at the intersection of convex optimization and (randomized) approximation algorithms. I am supported by an NSF GRFP grant.
Previously, I completed my undergrad at Princeton University (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.
Best arm identification for contaminated bandits
Jason Altschuler, Victor-Emmanuel Brunel, Alan Malek.
Online learning over a finite action set with limited switching
Jason Altschuler, Kunal Talwar.
To appear in Conference on Learning Theory (COLT), 2018.
Video of my COLT talk, slides, poster, COLT extended abstract
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Jason Altschuler, Jonathan Weed, Philippe Rigollet.
Neural Information Processing Systems (NIPS), 2017. (Selected for Spotlight presentation)
3-minute overview NIPS video, poster, code on Github
Inclusion of forbidden minors in random representable matroids
Jason Altschuler, Elizabeth Yang.
Discrete Mathematics, 2017.
Greedy column subset selection: new bounds and distributed algorithms
Jason Altschuler, Aditya Bhaskara, Gang Fu, Vahab Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam.
International Conference on Machine Learning (ICML), 2016.
Video of my ICML talk, slides, poster
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 (MIT 6.856), 2017.
Minimax rates for online learning with limited decision changes (superseded by this paper, to appear in COLT.)
Undergrad thesis for Princeton CS department, advised by Elad Hazan, 2016.
Probabilistic variants of Rota's so-called "critical problem" in combinatorics and coding theory
Undergrad thesis for Princeton math department, advised by Emmanuel Abbe, 2016.