1 code implementation • 19 May 2023 • Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
The effect is neglected by previous OIM works under IC and linear threshold models.
3 code implementations • 18 May 2022 • Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
Recent studies have shown that deep learning models such as RNNs and Transformers have brought significant performance gains for long-term forecasting of time series because they effectively utilize historical information.
Ranked #3 on Time Series Forecasting on ETTh2 (96) Univariate
no code implementations • 26 Oct 2020 • Gang Wang, Qunxi Dong, Jianfeng Wu, Yi Su, Kewei Chen, Qingtang Su, Xiaofeng Zhang, Jinguang Hao, Tao Yao, Li Liu, Caiming Zhang, Richard J Caselli, Eric M Reiman, Yalin Wang
With hippocampal UMIs, the estimated minimum sample sizes needed to detect a 25$\%$ reduction in the mean annual change with 80$\%$ power and two-tailed $P=0. 05$ are 116, 279 and 387 for the longitudinal $A\beta+$ AD, $A\beta+$ mild cognitive impairment (MCI) and $A\beta+$ CU groups, respectively.
no code implementations • 3 May 2019 • Tao Yao, Xiangwei Kong, Lianshan Yan, Wenjing Tang, Qi Tian
In this paper, to address above issues, we propose a supervised cross-modal hashing method based on matrix factorization dubbed Efficient Discrete Supervised Hashing (EDSH).
no code implementations • 7 Dec 2018 • Xue Wang, Mike Mingcheng Wei, Tao Yao
We propose a minimax concave penalized multi-armed bandit algorithm under generalized linear model (G-MCP-Bandit) for a decision-maker facing high-dimensional data in an online learning and decision-making process.
no code implementations • ICML 2018 • Xue Wang, Mingcheng Wei, Tao Yao
In addition, we develop a linear approximation method, the 2-step Weighted Lasso procedure, to identify the MCP estimator for the MCP-Bandit algorithm under non-i. i. d.