b'Rui Song'

research

∙ 07/27/2022

Partial Selfish Mining for More Profits

Mining attacks aim to gain an unfair share of extra rewards in the block...

Jiaping Yu, et al. ∙

research

∙ 06/17/2022

Edge-Aided Sensor Data Sharing in Vehicular Communication Networks

Sensor data sharing in vehicular networks can significantly improve the ...

Rui Song, et al. ∙

research

∙ 06/13/2022

Inference for change-plane regression

We establish the asymptotic behavior of change-plane estimators. Two typ...

Chaeryon Kang, et al. ∙

research

∙ 04/22/2022

Locally Aggregated Feature Attribution on Natural Language Model Understanding

With the growing popularity of deep-learning models, model understanding...

Sheng Zhang, et al. ∙

research

∙ 04/08/2022

Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes

In many important applications of precision medicine, the outcome of int...

Yu Zhou, et al. ∙

research

∙ 04/01/2022

Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS

In this paper, we introduce a federated learning framework coping with H...

Rui Song, et al. ∙

research

∙ 03/12/2022

Distributed Community Detection in Large Networks

Community detection for large networks is a challenging task due to the ...

Sheng Zhang, et al. ∙

research

∙ 03/04/2022

Adaptive Semi-Supervised Inference for Optimal Treatment Decisions with Electronic Medical Record Data

A treatment regime is a rule that assigns a treatment to patients based ...

Kevin Gunn, et al. ∙

research

∙ 02/26/2022

Safe Exploration for Efficient Policy Evaluation and Comparison

High-quality data plays a central role in ensuring the accuracy of polic...

Runzhe Wan, et al. ∙

research

∙ 02/26/2022

Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework

Online learning in large-scale structured bandits is known to be challen...

Runzhe Wan, et al. ∙

research

∙ 02/26/2022

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons

We consider reinforcement learning (RL) methods in offline domains witho...

Chengchun Shi, et al. ∙

research

∙ 02/25/2022

Exploratory Hidden Markov Factor Models for Longitudinal Mobile Health Data: Application to Adverse Posttraumatic Neuropsychiatric Sequelae

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among ...

Lin Ge, et al. ∙

research

∙ 02/25/2022

On Learning and Testing of Counterfactual Fairness through Data Preprocessing

Machine learning has become more important in real-life decision-making ...

Haoyu Chen, et al. ∙

research

∙ 02/22/2022

Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process

This paper is concerned with constructing a confidence interval for a ta...

Chengchun Shi, et al. ∙

research

∙ 02/21/2022

A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets

The two-sided markets such as ride-sharing companies often involve a gro...

Chengchun Shi, et al. ∙

research

∙ 02/21/2022

Rule Mining over Knowledge Graphs via Reinforcement Learning

Knowledge graphs (KGs) are an important source repository for a wide ran...

Lihan Chen, et al. ∙

research

∙ 02/12/2022

OctAttention: Octree-based Large-scale Contexts Model for Point Cloud Compression

In point cloud compression, sufficient contexts are significant for mode...

Chunyang Fu, et al. ∙

research

∙ 01/31/2022

Reinforcement Learning with Heterogeneous Data: Estimation and Inference

Reinforcement Learning (RL) has the promise of providing data-driven sup...

Elynn Y. Chen, et al. ∙

research

∙ 01/20/2022

Statistical Learning for Individualized Asset Allocation

We establish a high-dimensional statistical learning framework for indiv...

Yi Ding, et al. ∙

research

∙ 12/29/2021

HPRN: Holistic Prior-embedded Relation Network for Spectral Super-Resolution

Spectral super-resolution (SSR) refers to the hyperspectral image (HSI) ...

Chaoxiong Wu, et al. ∙

research

∙ 11/27/2021

A Review on Graph Neural Network Methods in Financial Applications

Keeping the individual features and the complicated relations, graph dat...

Jianian Wang, et al. ∙

research

∙ 11/19/2021

Flexible Inference of Optimal Individualized Treatment Strategy in Covariate Adjusted Randomization with Multiple Covariates

To maximize clinical benefit, clinicians routinely tailor treatment to t...

Trinetri Ghosh, et al. ∙

research

∙ 11/17/2021

Jump Interval-Learning for Individualized Decision Making

An individualized decision rule (IDR) is a decision function that assign...

Hengrui Cai, et al. ∙

research

∙ 11/06/2021

A Probit Tensor Factorization Model For Relational Learning

With the proliferation of knowledge graphs, modeling data with complex m...

Ye Liu, et al. ∙

research

∙ 11/06/2021

An Online Sequential Test for Qualitative Treatment Effects

Tech companies (e.g., Google or Facebook) often use randomized online ex...

Chengchun Shi, et al. ∙

research

∙ 10/29/2021

Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning

Evaluating the performance of an ongoing policy plays a vital role in ma...

Hengrui Cai, et al. ∙

research

∙ 09/02/2021

Online Testing of Subgroup Treatment Effects Based on Value Difference

Online A/B testing plays a critical role in the high-tech industry to gu...

Miao Yu, et al. ∙

research

∙ 08/13/2021

Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models

How to explore efficiently is a central problem in multi-armed bandits. ...

Runzhe Wan, et al. ∙

research

∙ 07/10/2021

On Estimating Optimal Regime for Treatment Initiation Time Based on Restricted Mean Residual Lifetime

When to initiate treatment on patients is an important problem in many m...

Xin Chen, et al. ∙

research

∙ 06/18/2021

Label Mask for Multi-Label Text Classification

One of the key problems in multi-label text classification is how to tak...

Rui Song, et al. ∙

research

∙ 05/30/2021

Periodic-GP: Learning Periodic World with Gaussian Process Bandits

We consider the sequential decision optimization on the periodic environ...

Hengrui Cai, et al. ∙

research

∙ 05/27/2021

Pattern Transfer Learning for Reinforcement Learning in Order Dispatching

Order dispatch is one of the central problems to ride-sharing platforms....

Runzhe Wan, et al. ∙

research

∙ 05/10/2021

Deeply-Debiased Off-Policy Interval Estimation

Off-policy evaluation learns a target policy's value with a historical d...

Chengchun Shi, et al. ∙

research

∙ 04/21/2021

GEAR: On Optimal Decision Making with Auxiliary Data

Personalized optimal decision making, finding the optimal decision rule ...

Hengrui Cai, et al. ∙

research

∙ 04/21/2021

Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome

We consider the optimal decision-making problem in a primary sample of i...

Hengrui Cai, et al. ∙

research

∙ 04/19/2021

ASFM-Net: Asymmetrical Siamese Feature Matching Network for Point Completion

We tackle the problem of object completion from point clouds and propose...

Yaqi Xia, et al. ∙

research

∙ 04/03/2021

Topological Regularization for Graph Neural Networks Augmentation

The complexity and non-Euclidean structure of graph data hinder the deve...

Rui Song, et al. ∙

research

∙ 10/29/2020

Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space

We consider off-policy evaluation (OPE) in continuous action domains, su...

Hengrui Cai, et al. ∙

research

∙ 10/19/2020

Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning

Open attribute value extraction for emerging entities is an important bu...

Ye Liu, et al. ∙

research

∙ 10/14/2020

Statistical Inference for Online Decision Making via Stochastic Gradient Descent

Online decision making aims to learn the optimal decision rule by making...

Haoyu Chen, et al. ∙

research

∙ 10/14/2020

Statistical Inference for Online Decision-Making: In a Contextual Bandit Setting

Online decision-making problem requires us to make a sequence of decisio...

Haoyu Chen, et al. ∙

research

∙ 09/09/2020

Multi-Objective Reinforcement Learning for Infectious Disease Control with Application to COVID-19 Spread

Severe infectious diseases such as the novel coronavirus (COVID-19) pose...

Runzhe Wan, et al. ∙

research

∙ 07/19/2020

Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health

In this article, we propose novel structural nested models to estimate c...

Liangyu Zhu, et al. ∙

research

∙ 07/19/2020

Kernel Assisted Learning for Personalized Dose Finding

An individualized dose rule recommends a dose level within a continuous ...

Liangyu Zhu, et al. ∙

research

∙ 05/19/2020

AdaptiveWeighted Attention Network with Camera Spectral Sensitivity Prior for Spectral Reconstruction from RGB Images

Recent promising effort for spectral reconstruction (SR) focuses on lear...

Jiaojiao Li, et al. ∙

research

∙ 02/09/2020

A New Framework for Online Testing of Heterogeneous Treatment Effect

We propose a new framework for online testing of heterogeneous treatment...

Miao Yu, et al. ∙

research

∙ 02/05/2020

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making

The Markov assumption (MA) is fundamental to the empirical validity of r...

Chengchun Shi, et al. ∙

research

∙ 02/05/2020

A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing

A/B testing, or online experiment is a standard business strategy to com...

Chengchun Shi, et al. ∙

research

∙ 03/12/2019

Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data

Non-probability samples become increasingly popular in survey statistics...

Shu Yang, et al. ∙

research

∙ 12/06/2018

The USTC-NEL Speech Translation system at IWSLT 2018

This paper describes the USTC-NEL system to the speech translation task ...

Dan Liu, et al. ∙

Rui Song

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