no code implementations • 30 Mar 2024 • Ruqian Zhang, Yijiao Zhang, Annie Qu, Zhongyi Zhu, Juan Shen
Distinguished from existing work, CONCERT is a one-step procedure, which achieves variable selection and information transfer simultaneously.
no code implementations • 19 Dec 2023 • Hanwen Ye, Tatiana Moreno, Adrianne Alpern, Louis Ehwerhemuepha, Annie Qu
However, few topic models are built for longitudinal settings, and they fail to keep consistent topics and capture temporal trajectories for each document.
no code implementations • 21 Nov 2023 • Jiuchen Zhang, Fei Xue, Qi Xu, Jung-Ah Lee, Annie Qu
In this paper, we propose an individualized dynamic latent factor model for irregular multi-resolution time series data to interpolate unsampled measurements of time series with low resolution.
no code implementations • 30 Oct 2023 • Hanwen Ye, Wenzhuo Zhou, Ruoqing Zhu, Annie Qu
In particular, the proposed learning scheme builds a more general framework which includes the popular outcome weighted learning framework as a special case of ours.
no code implementations • 28 Sep 2023 • Wenzhuo Zhou, Annie Qu
From a theoretical standpoint, we provide instance-dependent regret bounds with general function approximation, which shows that our algorithm can learn a best-effort policy that is able to compete against any comparator policy that is covered by batch data.
no code implementations • 23 Sep 2023 • Wenzhuo Zhou, Yuhan Li, Ruoqing Zhu, Annie Qu
This task faces two primary challenges: providing a comprehensive and rigorous error quantification in CI estimation, and addressing the distributional shift that results from discrepancies between the distribution induced by the target policy and the offline data-generating process.
no code implementations • 23 Sep 2023 • Wenzhuo Zhou, Annie Qu, Keiland W. Cooper, Norbert Fortin, Babak Shahbaba
Graph Neural Networks (GNNs) have achieved promising performance in a variety of graph-focused tasks.
no code implementations • 8 Nov 2021 • Yujia Deng, Yubai Yuan, Haoda Fu, Annie Qu
In particular, we augment the queried constraints by generating more pairwise labels to provide additional information in learning a metric to enhance clustering performance.
no code implementations • 7 Nov 2021 • Yubai Yuan, Annie Qu
Link prediction infers potential links from observed networks, and is one of the essential problems in network analyses.
no code implementations • 20 Oct 2021 • Wenzhuo Zhou, Ruoqing Zhu, Annie Qu
To address these challenges, we propose a Proximal Temporal consistency Learning (pT-Learning) framework to estimate an optimal regime that is adaptively adjusted between deterministic and stochastic sparse policy models.
no code implementations • 17 May 2021 • Yutong Li, Ruoqing Zhu, Annie Qu, Mike Yeh
We represent each dermoscopic image as the style image and transfer the style of the lesion onto a homogeneous content image.
no code implementations • 6 Nov 2020 • Xuan Bi, Gediminas Adomavicius, William Li, Annie Qu
Due to accessible big data collections from consumers, products, and stores, advanced sales forecasting capabilities have drawn great attention from many companies especially in the retail business because of its importance in decision making.
no code implementations • 14 Jan 2020 • Fei Xue, Yanqing Zhang, Wenzhuo Zhou, Haoda Fu, Annie Qu
An optimal dynamic treatment regime (DTR) consists of a sequence of decision rules in maximizing long-term benefits, which is applicable for chronic diseases such as HIV infection or cancer.
no code implementations • 21 Mar 2019 • Xiwei Tang, Xuan Bi, Annie Qu
This work is motivated by multimodality breast cancer imaging data, which is quite challenging in that the signals of discrete tumor-associated microvesicles (TMVs) are randomly distributed with heterogeneous patterns.
no code implementations • 7 May 2018 • Jack Yutong Li, Ruoqing Zhu, Annie Qu, Han Ye, Zhankun Sun
The subjects can then be interpreted as a non-subtractive linear combination of orthogonal basis topic vectors.
no code implementations • 5 Nov 2017 • Xuan Bi, Annie Qu, Xiaotong Shen
Recommender systems have been widely adopted by electronic commerce and entertainment industries for individualized prediction and recommendation, which benefit consumers and improve business intelligence.