4 papers
Adaptive Estimation and Learning under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Duy Nguyen +2
In this paper, we study the problem of estimation and learning under temporal distribution shift. Consider an observation sequence of length , which is a noisy realization of a…
Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach
Dheeraj Baby, Boran Han, Shuai Zhang +3
We study the well-motivated problem of online distribution shift in which the data arrive in batches and the distribution of each batch can change arbitrarily over time. Since the…
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
Ruihan Wu, Siddhartha Datta, Yi Su +3
This paper addresses the prevalent issue of label shift in an online setting with missing labels, where data distributions change over time and obtaining timely labels is challengi…
Online Matrix Completion: A Collaborative Approach with Hott Items
Dheeraj Baby, Soumyabrata Pal
We investigate the low rank matrix completion problem in an online setting with users, items, rounds, and an unknown rank- reward matrix ${R}\in \mathbb{R}^{{M…