**Amazon AWS- Applied Scientist Intern, Palo Alto, USA.**
*May- August 2017*

I worked under the supervision of Professor Animashree Anandkumar.

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]

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

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 •