357 citations · 2.8k across the 94 of their papers we have counts for
97 papers
AdANNS: A Framework for Adaptive Semantic Search
Aniket Rege, Aditya Kusupati, Sharan Ranjit S +5
Web-scale search systems learn an encoder to embed a given query which is then hooked into an approximate nearest neighbor search (ANNS) pipeline to retrieve similar data points. T…
Multi-Task Differential Privacy Under Distribution Skew
Walid Krichene, Prateek Jain, Shuang Song +3
We study the problem of multi-task learning under user-level differential privacy, in which users contribute data to tasks, each involving a subset of users. One important…
Simplicity Bias in 1-Hidden Layer Neural Networks
Depen Morwani, Jatin Batra, Prateek Jain +1
Recent works have demonstrated that neural networks exhibit extreme simplicity bias(SB). That is, they learn only the simplest features to solve a task at hand, even in the presenc…
Near Optimal Private and Robust Linear Regression
Xiyang Liu, Prateek Jain, Weihao Kong +2
We study the canonical statistical estimation problem of linear regression from i.i.d.~examples under -differential privacy when some response variables are ad…
Variational Quantum Algorithms for Chemical Simulation and Drug Discovery
Hasan Mustafa, Sai Nandan Morapakula, Prateek Jain +1
Quantum computing has gained a lot of attention recently, and scientists have seen potential applications in this field using quantum computing for Cryptography and Communication t…
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks
Sravanti Addepalli, Anshul Nasery, R. Venkatesh Babu +2
Deep Neural Networks are known to be brittle to even minor distribution shifts compared to the training distribution. While one line of work has demonstrated that Simplicity Bias (…