12 citations · 52 across the 11 of their papers we have counts for
11 papers · 1 filter
Efficient List-Decodable Regression using Batches
Abhimanyu Das, Ayush Jain, Weihao Kong +1
We begin the study of list-decodable linear regression using batches. In this setting only an fraction of the batches are genuine. Each genuine batch contains …
DP-PCA: Statistically Optimal and Differentially Private PCA
Xiyang Liu, Weihao Kong, Prateek Jain +1
We study the canonical statistical task of computing the principal component from i.i.d.~data in dimensions under -differential privacy. Although extensive…
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics
Jonathan Hayase, Weihao Kong, Raghav Somani +1
Modern machine learning increasingly requires training on a large collection of data from multiple sources, not all of which can be trusted. A particularly concerning scenario is w…
Online Model Selection for Reinforcement Learning with Function Approximation
Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar +2
Deep reinforcement learning has achieved impressive successes yet often requires a very large amount of interaction data. This result is perhaps unsurprising, as using complicated…
Robust Meta-learning for Mixed Linear Regression with Small Batches
Weihao Kong, Raghav Somani, Sham Kakade +1
A common challenge faced in practical supervised learning, such as medical image processing and robotic interactions, is that there are plenty of tasks but each task cannot afford…
Meta-learning for mixed linear regression
Weihao Kong, Raghav Somani, Zhao Song +2
In modern supervised learning, there are a large number of tasks, but many of them are associated with only a small amount of labeled data. These include data from medical image pr…