16 citations · 21 across the 8 of their papers we have counts for
8 papers
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…
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…
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)…
Robust Lipschitz Bandits to Adversarial Corruptions
Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
Lipschitz bandit is a variant of stochastic bandits that deals with a continuous arm set defined on a metric space, where the reward function is subject to a Lipschitz constraint.…
Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits
Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
In stochastic contextual bandits, an agent sequentially makes actions from a time-dependent action set based on past experience to minimize the cumulative regret. Like many other m…
Rethinking Adam: A Twofold Exponential Moving Average Approach
Yizhou Wang, Yue Kang, Can Qin +4
Adaptive gradient methods, e.g. \textsc{Adam}, have achieved tremendous success in machine learning. Scaling the learning rate element-wisely by a certain form of second moment est…
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms
Qin Ding, Yue Kang, Yi-Wei Liu +3
The stochastic contextual bandit problem, which models the trade-off between exploration and exploitation, has many real applications, including recommender systems, online adverti…
Sequence-based deep learning antibody design for in silico antibody affinity maturation
Yue Kang, Dawei Leng, Jinjiang Guo +1
Antibody therapeutics has been extensively studied in drug discovery and development within the past decades. One increasingly popular focus in the antibody discovery pipeline is t…