A Fast Sampling Algorithm for Maximum Inner Product Search. - Qin Ding 002; Hsiang-Fu Yu; Cho-Jui Hsieh (AISTATS, 2019)

Multiscale Non-stationary Stochastic Bandits. - Qin Ding 002; Cho-Jui Hsieh; James Sharpnack (CoRR, 2020)

An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. - Qin Ding 002; Cho-Jui Hsieh; James Sharpnack (AISTATS, 2021)

Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. - Qin Ding 002; Yi-Wei Liu; Cho-Jui Hsieh; James Sharpnack (CoRR, 2021)

Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. - Qin Ding 002; Cho-Jui Hsieh; James Sharpnack (AISTATS, 2022)

Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. - Qin Ding 002; Yue Kang 002; Yi-Wei Liu; Thomas Chun Man Lee; Cho-Jui Hsieh; James Sharpnack (NeurIPS, 2022)