most citedEfficient Frameworks for Generalized Low-Rank Matrix Bandit Problems

2 citations · 2 across the 2 of their papers we have counts for

collaborators

3 papers

stat.ML2024

Low-rank Matrix Bandits with Heavy-tailed Rewards

Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee

In stochastic low-rank matrix bandit, the expected reward of an arm is equal to the inner product between its feature matrix and some unknown by low-rank parameter matr…

stat.ML2024★ 2 cited

Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems

Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee

In the stochastic contextual low-rank matrix bandit problem, the expected reward of an action is given by the inner product between the action's feature matrix and some fixed, but…

cs.LG2023

Try with Simpler -- An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detection

Lin Yang, Junjie Chen, Shutao Gao +4

The rapid growth of deep learning (DL) has spurred interest in enhancing log-based anomaly detection. This approach aims to extract meaning from log events (log message templates)…