Mikhail Khodak

Advances and Open Problems in Federated Learning

Peter Kairouz, H. Brendan McMahan, Brendan Avent et al. · Foundations and Trends® in Machine Learning · 2020 · 4.2K citations · Full text

A Theoretical Analysis of Contrastive Unsupervised Representation Learning

Sanjeev Arora, Hrishikesh Khandeparkar, Mikhail Khodak et al. · arXiv (Cornell University) · 2019 · 205 citations · Full text

Structured Prediction, Engineering, Machine Learning +16

A Large Self-Annotated Corpus for Sarcasm

Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli · arXiv (Cornell University) · 2017 · 133 citations · Full text

Engineering, Communication, Multimodal Sentiment Analysis +19

A Large Self-Annotated Corpus for Sarcasm

Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli · arXiv (Cornell University) · 2017 · 70 citations · Full text

Natural Language Processing, Engineering, Large Self-annotated Corpus +9

Provable Guarantees for Gradient-Based Meta-Learning.

Maria-Florina Balcan, Mikhail Khodak, Ameet Talwalkar · International Conference on Machine Learning · 2019 · 50 citations

Artificial Intelligence, Engineering, Machine Learning +5