b'Rui Song'

research

∙ 08/20/2023

A Survey on Fairness in Large Language Models

Large language models (LLMs) have shown powerful performance and develop...

0 Yingji Li, et al. ∙

research

∙ 08/19/2023

Pseudo Flow Consistency for Self-Supervised 6D Object Pose Estimation

Most self-supervised 6D object pose estimation methods can only work wit...

0 Yang Hai, et al. ∙

research

∙ 07/27/2023

LinkDID: A Privacy-Preserving, Sybil-Resistant and Key-Recoverable Decentralized Identity Scheme

Decentralized identity mechanisms endeavor to endow users with complete ...

0 Rui Song, et al. ∙

research

∙ 06/23/2023

Shape-Constraint Recurrent Flow for 6D Object Pose Estimation

Most recent 6D object pose methods use 2D optical flow to refine their r...

0 Yang Hai, et al. ∙

research

∙ 05/19/2023

V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection

Machine learning (ML) has revolutionized transportation systems, enablin...

0 Rui Song, et al. ∙

research

∙ 04/04/2023

FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems

Bird's eye view (BEV) perception is becoming increasingly important in t...

0 Rui Song, et al. ∙

research

∙ 04/02/2023

Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring

With the growing needs of online A/B testing to support the innovation i...

0 Runzhe Wan, et al. ∙

research

∙ 03/22/2023

Rigidity-Aware Detection for 6D Object Pose Estimation

Most recent 6D object pose estimation methods first use object detection...

0 Yang Hai, et al. ∙

research

∙ 03/14/2023

V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception

Modern perception systems of autonomous vehicles are known to be sensiti...

0 Runsheng Xu, et al. ∙

research

∙ 02/03/2023

Multiplier Bootstrap-based Exploration

Despite the great interest in the bandit problem, designing efficient al...

0 Runzhe Wan, et al. ∙

research

∙ 01/31/2023

A Reinforcement Learning Framework for Dynamic Mediation Analysis

Mediation analysis learns the causal effect transmitted via mediator var...

10 Lin Ge, et al. ∙

research

∙ 01/29/2023

On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs

Heterogeneity and comorbidity are two interwoven challenges associated w...

0 Richard A Watson, et al. ∙

research

∙ 01/03/2023

Deep Spectral Q-learning with Application to Mobile Health

Dynamic treatment regimes assign personalized treatments to patients seq...

0 Yuhe Gao, et al. ∙

research

∙ 12/30/2022

Heterogeneous Synthetic Learner for Panel Data

In the new era of personalization, learning the heterogeneous treatment ...

0 Ye Shen, et al. ∙

research

∙ 12/29/2022

An Instrumental Variable Approach to Confounded Off-Policy Evaluation

Off-policy evaluation (OPE) is a method for estimating the return of a t...

0 Yang Xu, et al. ∙

research

∙ 12/29/2022

Quantile Off-Policy Evaluation via Deep Conditional Generative Learning

Off-Policy evaluation (OPE) is concerned with evaluating a new target po...

0 Yang Xu, et al. ∙

research

∙ 12/25/2022

Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies

Latent factor model estimation typically relies on either using domain k...

0 Runzhe Wan, et al. ∙

research

∙ 12/11/2022

ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals

Federated learning enables cooperative training among massively distribu...

0 Rui Song, et al. ∙

research

∙ 09/23/2022

Sure Screening for Transelliptical Graphical Models

We propose a sure screening approach for recovering the structure of a t...

0 Yuxiang Xie, et al. ∙

research

∙ 07/27/2022

Partial Selfish Mining for More Profits

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

0 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 ...

0 Rui Song, et al. ∙

research

∙ 06/13/2022

Inference for change-plane regression

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

0 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...

0 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...

0 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...

0 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 ...

0 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 ...

0 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...

0 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...

0 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...

0 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 ...

0 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 ...

0 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...

0 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...

0 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...

9 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...

0 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...

10 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...

0 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) ...

8 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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. ...

0 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...

0 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...

0 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...

0 Hengrui Cai, et al. ∙

Rui Song

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