Internship

Amazon AWS- Applied Scientist Intern, Palo Alto, USA. May- August 2017
I worked under the supervision of Professor Animashree Anandkumar.


Conference papers

Number of Connected Components in a Graph: Estimation via Counting Patterns
  Ashish Khetan, Sewoong Oh
  working paper, 2018

PacGAN: The power of two samples in generative adversarial networks
   Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh
   working paper, 2018, [code]

Learning From Noisy Singly-labeled Data
   Ashish Khetan, Zachary C. Lipton, Anima Anandkumar
   ICLR, 2018, [code], [IPython notebook], [Poster]

Matrix Norm Estimation from a Few Entries
   Ashish Khetan, Sewoong Oh
   NIPS, 2017 (Spotlight presentation), [video], [code]

Computational and Statistical Tradeoffs in Learning to Rank
   Ashish Khetan, Sewoong Oh
   NIPS, 2016, [video]

Achieving Budget-optimality with Adaptive Schemes in Crowdsourcing
   Ashish Khetan, Sewoong Oh
   NIPS, 2016, [video]

Data-driven Rank Breaking for Efficient Rank Aggregation
   Ashish Khetan, Sewoong Oh
   ICML, 2016, [slides]


Journal papers

Data-driven Rank Breaking for Efficient Rank Aggregation
  Ashish Khetan, Sewoong Oh
   Journal of Machine Learning Research, 2016

Spectrum Estimation from a Few Entries
   Ashish Khetan, Sewoong Oh
   Submitted to Journal of Machine Learning Research, 2018

Computational and Statistical Tradeoffs in Learning to Rank
   Ashish Khetan, Sewoong Oh
   Submitted to Journal of Machine Learning Research, 2017

Achieving Budget-optimality with Adaptive Schemes in Crowdsourcing
  Ashish Khetan, Sewoong Oh
   Submitted to Operations Research

Markov Chain Choice Model from Pairwise Comparisons
   Ashish Khetan, Sewoong Oh
   Submitted to IEEE Transactions


Selected coursework

Machine Learning Theory • Statistical Learning Theory • Inference in Graphical Models • Algorithms for Inference • Pattern Recognition • Machine Learning • ML in NLP • Convex Optimization • Integer Programming • Linear Programming • Theory of Probability • Real Analysis • Random Processes • Information Theory • Graphs Networks & Algorithms •