67 citations · 190 across the 18 of their papers we have counts for
21 papers
Minimizing Change-Point Estimation Error
Hock Peng Chan
In this paper we consider change-points in multiple sequences with the objective of minimizing the estimation error of a sequence by making use of information from other sequences.…
Likelihood Scores for Sparse Signal and Change-Point Detection
Shouri Hu, Jingyan Huang, Hao Chen +1
We consider here the identification of change-points on large-scale data streams. The objective is to find the most efficient way of combining information across data stream so tha…
Optimal UCB Adjustments for Large Arm Sizes
Hock Peng Chan, Shouri Hu
The regret lower bound of Lai and Robbins (1985), the gold standard for checking optimality of bandit algorithms, considers arm size fixed as sample size goes to infinity. We show…
Infinite Arms Bandit: Optimality via Confidence Bounds
Hock Peng Chan, Shouri Hu
Berry et al. (1997) initiated the development of the infinite arms bandit problem. They derived a regret lower bound of all allocation strategies for Bernoulli rewards with uniform…
Multi-sequence segmentation via score and higher-criticism tests
Hock-Peng Chan, Hao Chen
We propose local segmentation of multiple sequences sharing a common time- or location-index, building upon the single sequence local segmentation methods of Niu and Zhang (2012) a…
The Multi-Armed Bandit Problem: An Efficient Non-Parametric Solution
Hock Peng Chan
Lai and Robbins (1985) and Lai (1987) provided efficient parametric solutions to the multi-armed bandit problem, showing that arm allocation via upper confidence bounds (UCB) achie…