no code implementations • 16 Feb 2024 • Chao Qin, Daniel Russo
Practitioners conducting adaptive experiments often encounter two competing priorities: reducing the cost of experimentation by effectively assigning treatments during the experiment itself, and gathering information swiftly to conclude the experiment and implement a treatment across the population.
no code implementations • 6 Feb 2024 • Chuang Li, Yichen Wei, Chao Qin, ShiFan Chen, Xiaolong Shao
In response to infections, host cells dictate a variety of cell death pathways, including apoptosis, pyroptosis, necrosis, and lysosomal cell death, which are essential for amplifying immune responses and controlling pathogen dissemination.
no code implementations • 30 Oct 2023 • Chao Qin, Wei You
Using dual variables, we characterize the necessary and sufficient conditions for an allocation to be optimal.
1 code implementation • 9 Sep 2023 • Chao Qin, Jiale Cao, Huazhu Fu, Rao Muhammad Anwer, Fahad Shahbaz Khan
Existing video-based breast lesion detection approaches typically perform temporal feature aggregation of deep backbone features based on the self-attention operation.
no code implementations • 2 Mar 2023 • Chao Qin
Best arm identification or pure exploration problems have received much attention in the COLT community since Bubeck et al. (2009) and Audibert et al. (2010).
1 code implementation • 24 May 2022 • Wei You, Chao Qin, ZiHao Wang, Shuoguang Yang
We consider the best-k-arm identification problem for multi-armed bandits, where the objective is to select the exact set of k arms with the highest mean rewards by sequentially allocating measurement effort.
no code implementations • 22 May 2022 • Botao Hao, Tor Lattimore, Chao Qin
Information-directed sampling (IDS) has recently demonstrated its potential as a data-efficient reinforcement learning algorithm.
no code implementations • 2 Mar 2022 • Chao Qin, Zheng Wen, Xiuyuan Lu, Benjamin Van Roy
Ensemble sampling serves as a practical approximation to Thompson sampling when maintaining an exact posterior distribution over model parameters is computationally intractable.
no code implementations • 18 Feb 2022 • Chao Qin, Daniel Russo
We investigate experiments that are designed to select a treatment arm for population deployment.
no code implementations • 12 Jan 2022 • Masahiro Kato, Kaito Ariu, Masaaki Imaizumi, Masahiro Nomura, Chao Qin
We show that a strategy following the Neyman allocation rule (Neyman, 1934) is asymptotically optimal when the gap between the expected rewards is small.
1 code implementation • 18 Nov 2021 • Junpei Komiyama, Kaito Ariu, Masahiro Kato, Chao Qin
We consider best arm identification in the multi-armed bandit problem.
no code implementations • 16 Sep 2021 • Kaito Ariu, Masahiro Kato, Junpei Komiyama, Kenichiro McAlinn, Chao Qin
We consider the "policy choice" problem -- otherwise known as best arm identification in the bandit literature -- proposed by Kasy and Sautmann (2021) for adaptive experimental design.
no code implementations • 20 Jul 2021 • Zheng Wen, Ian Osband, Chao Qin, Xiuyuan Lu, Morteza Ibrahimi, Vikranth Dwaracherla, Mohammad Asghari, Benjamin Van Roy
A fundamental challenge for any intelligent system is prediction: given some inputs, can you predict corresponding outcomes?
no code implementations • 30 Mar 2020 • Xiyi Wei, Yu-Tian Xiao, Jian Wang, Rui Chen, Wei zhang, Yue Yang, Daojun Lv, Chao Qin, Di Gu, Bo Zhang, Weidong Chen, Jianquan Hou, Ninghong Song, Guohua Zeng, Shancheng Ren
Objective: To conduct a meta-analysis of current studies that examined sex differences in severity and mortality in patients with COVID-19, and identify potential mechanisms underpinning these differences.
no code implementations • NeurIPS 2017 • Chao Qin, Diego Klabjan, Daniel Russo
To overcome this shortcoming, we introduce a simple modification of the expected improvement algorithm.