activity
20052025
most citedRank-Sparsity Incoherence for Matrix Decomposition

688 citations · 1.9k across the 57 of their papers we have counts for

collaborators

61 papers

cs.LG2025

Asymptotically-Optimal Gaussian Bandits with Side Observations

Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis +2

We study the problem of Gaussian bandits with general side information, as first introduced by Wu, Szepesvari, and Gyorgy. In this setting, the play of an arm reveals information a…

cs.LG2025

InfoPO: On Mutual Information Maximization for Large Language Model Alignment

Teng Xiao, Zhen Ge, Sujay Sanghavi +5

We study the post-training of large language models (LLMs) with human preference data. Recently, direct preference optimization and its variants have shown considerable promise in…

cs.LG2023

Finite-Time Logarithmic Bayes Regret Upper Bounds

Alexia Atsidakou, Branislav Kveton, Sumeet Katariya +2

We derive the first finite-time logarithmic Bayes regret upper bounds for Bayesian bandits. In a multi-armed bandit, we obtain and upper bounds for…

cs.LG2022★ 2 cited

Bayesian Fixed-Budget Best-Arm Identification

Alexia Atsidakou, Sumeet Katariya, Sujay Sanghavi +1

Fixed-budget best-arm identification (BAI) is a bandit problem where the agent maximizes the probability of identifying the optimal arm within a fixed budget of observations. In th…

cs.IR2022

On the Value of Behavioral Representations for Dense Retrieval

Nan Jiang, Dhivya Eswaran, Choon Hui Teo +4

We consider text retrieval within dense representational space in real-world settings such as e-commerce search where (a) document popularity and (b) diversity of queries associate…

cs.LG2022★ 1 cited

Beyond Uniform Lipschitz Condition in Differentially Private Optimization

Rudrajit Das, Satyen Kale, Zheng Xu +2

Most prior results on differentially private stochastic gradient descent (DP-SGD) are derived under the simplistic assumption of uniform Lipschitzness, i.e., the per-sample gradien…