Prateek Jain
Prateek Jain is a research scientist at Google Research India and an adjunct faculty member at IIT Kanpur. Earlier, he was a Senior Principal Researcher at Microsoft Research India. He obtained his PhD degree from the Computer Science department at UT Austin and his BTech degree from IIT Kanpur. He works in the areas of large-scale and non-convex optimization, high-dimensional statistics, and ML for resource-constrained devices. He wrote a monograph on Non-convex Optimization in Machine Learning summarizing many of his results in non-convex optimization. Prateek regularly serves on the senior program committee of top ML conferences and is an action editor for JMLR, and an associate editor for SIMODS. His work has won ICML-2007, CVPR-2008 best student paper award and more recently his work on alternating minimization has been selected as the 2020 Best Paper by the IEEE Signal Processing Society.
Please visit prateekjain.org for my personal website.
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Google
Dual-Encoders for Extreme Multi-label Classification
Nilesh Gupta
Devvrit Khatri
Inderjit Dhillon
International Conference on Learning Representations (ICLR) (2024)
LEARNING AN INVERTIBLE OUTPUT MAPPING CAN MITIGATE SIMPLICITY BIAS IN NEURAL NETWORKS
Anshul Nasery
Sravanti Addepalli
Will be submitted to ICLR 2023 (2023) (to appear)
Matryoshka Representation Learning
Aditya Kusupati
Gantavya Bhatt
Aniket Rege
Matthew Wallingford
Aditya Sinha
Vivek Ramanujan
William Howard-Snyder
Sham Kakade
Ali Farhadi
NeurIPS 2022 (2022)
Domain-Agnostic Contrastive Representations for Learning from Label Proportions
Jay Nandy
Jatin Chauhan
Balaraman Ravindran
Proc. CIKM 2022
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes
Aditya Kusupati
Matthew Wallingford
Vivek Ramanujan
Raghav Somani
Jae Sung Park
Krishna Pillutla
Sham Kakade
Ali Farhadi
Advances in Neural Information Processing Systems 34 (2021)
