b'Yan Zheng'

research

∙ 08/20/2023

Adversarial Collaborative Filtering for Free

Collaborative Filtering (CF) has been successfully used to help users di...

0 Huiyuan Chen, et al. ∙

research

∙ 08/01/2023

BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization

Evolutionary reinforcement learning (ERL) algorithms recently raise atte...

0 Junyi Wang, et al. ∙

research

∙ 07/18/2023

Sharpness-Aware Graph Collaborative Filtering

Graph Neural Networks (GNNs) have achieved impressive performance in col...

0 Huiyuan Chen, et al. ∙

research

∙ 06/27/2023

Prioritized Trajectory Replay: A Replay Memory for Data-driven Reinforcement Learning

In recent years, data-driven reinforcement learning (RL), also known as ...

0 Jinyi Liu, et al. ∙

research

∙ 06/12/2023

Ensemble-based Offline-to-Online Reinforcement Learning: From Pessimistic Learning to Optimistic Exploration

Offline reinforcement learning (RL) is a learning paradigm where an agen...

0 Kai Zhao, et al. ∙

research

∙ 06/10/2023

HIPODE: Enhancing Offline Reinforcement Learning with High-Quality Synthetic Data from a Policy-Decoupled Approach

Offline reinforcement learning (ORL) has gained attention as a means of ...

0 Shixi Lian, et al. ∙

research

∙ 06/09/2023

In-Sample Policy Iteration for Offline Reinforcement Learning

Offline reinforcement learning (RL) seeks to derive an effective control...

0 Xiaohan Hu, et al. ∙

research

∙ 01/27/2023

Neural Episodic Control with State Abstraction

Existing Deep Reinforcement Learning (DRL) algorithms suffer from sample...

2 Zhuo Li, et al. ∙

research

∙ 12/08/2022

TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems

There has been an explosion of interest in designing various Knowledge G...

0 Huiyuan Chen, et al. ∙

research

∙ 12/08/2022

Denoising Self-attentive Sequential Recommendation

Transformer-based sequential recommenders are very powerful for capturin...

0 Huiyuan Chen, et al. ∙

research

∙ 10/26/2022

ERL-Re^2: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation

Deep Reinforcement Learning (Deep RL) and Evolutionary Algorithm (EA) ar...

0 Pengyi Li, et al. ∙

research

∙ 10/06/2022

Neural Volumetric Mesh Generator

Deep generative models have shown success in generating 3D shapes with d...

51 Yan Zheng, et al. ∙

research

∙ 10/02/2022

EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model

Unsupervised reinforcement learning (URL) poses a promising paradigm to ...

0 Yifu Yuan, et al. ∙

research

∙ 09/16/2022

Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes

Lying on the heart of intelligent decision-making systems, how policy is...

0 Min Zhang, et al. ∙

research

∙ 08/15/2022

Energy Savings When Migrating Workloads to the Cloud

In the cloud environment, data centers are efficiently manipulated by cl...

0 Yan Zheng, et al. ∙

research

∙ 06/06/2022

HIFI-Net: A Novel Network for Enhancement to Underwater Images

A novel network for enhancement to underwater images is proposed in this...

0 Jiajia Zhou, et al. ∙

research

∙ 05/05/2022

Relational Representation Learning in Visually-Rich Documents

Relational understanding is critical for a number of visually-rich docum...

0 Xin Li, et al. ∙

research

∙ 04/06/2022

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations

Deep Reinforcement Learning (DRL) has been a promising solution to many ...

0 Tong Sang, et al. ∙

research

∙ 03/17/2022

Revealing Reliable Signatures by Learning Top-Rank Pairs

Signature verification, as a crucial practical documentation analysis ta...

0 Xiaotong Ji, et al. ∙

research

∙ 03/16/2022

PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration

Learning to collaborate is critical in Multi-Agent Reinforcement Learnin...

0 Pengyi Li, et al. ∙

research

∙ 12/24/2021

Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series

The matrix profile is an effective data mining tool that provides simila...

6 Chin-Chia Michael Yeh, et al. ∙

research

∙ 12/06/2021

ED2: An Environment Dynamics Decomposition Framework for World Model Construction

Model-based reinforcement learning methods achieve significant sample ef...

0 Cong Wang, et al. ∙

research

∙ 11/19/2021

Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning

Value estimation is one key problem in Reinforcement Learning. Albeit ma...

0 Tong Sang, et al. ∙

research

∙ 09/21/2021

Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks

Predicting metrics associated with entities' transnational behavior with...

8 Chin-Chia Michael Yeh, et al. ∙

research

∙ 09/12/2021

HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation

Discrete-continuous hybrid action space is a natural setting in many pra...

0 Boyan Li, et al. ∙

research

∙ 05/24/2021

Towards Book Cover Design via Layout Graphs

Book covers are intentionally designed and provide an introduction to a ...

0 Wensheng Zhang, et al. ∙

research

∙ 04/06/2021

VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations

Word vector embeddings have been shown to contain and amplify biases in ...

4 Archit Rathore, et al. ∙

research

∙ 11/05/2020

Merchant Category Identification Using Credit Card Transactions

Digital payment volume has proliferated in recent years with the rapid g...

7 Chin-Chia Michael Yeh, et al. ∙

research

∙ 05/14/2020

Continuous Multiagent Control using Collective Behavior Entropy for Large-Scale Home Energy Management

With the increasing popularity of electric vehicles, distributed energy ...

3 Jianwen Sun, et al. ∙

research

∙ 05/14/2020

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

Adversarial attacks against conventional Deep Learning (DL) systems and ...

2 Jianwen Sun, et al. ∙

research

∙ 02/18/2020

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge

Reinforcement learning agents usually learn from scratch, which requires...

15 Peng Zhang, et al. ∙

research

∙ 10/20/2019

Diverse Behavior Is What Game AI Needs: Generating Varied Human-Like Playing Styles Using Evolutionary Multi-Objective Deep Reinforcement Learning

Designing artificial intelligence for games (Game AI) has been long reco...

0 Yan Zheng, et al. ∙

research

∙ 10/13/2019

Feature Detection and Attenuation in Embeddings

Embedding is one of the fundamental building blocks for data analysis ta...

14 Yuwei Wang, et al. ∙

research

∙ 08/09/2019

Gradient Boosting Survival Tree with Applications in Credit Scoring

Credit scoring (Thomas et al., 2002) plays a vital role in the field of ...

0 Miaojun Bai, et al. ∙

research

∙ 11/28/2018

Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data

Detecting semantic parts of an object is a challenging task in computer ...

12 Yutong Bai, et al. ∙

research

∙ 09/25/2018

Hierarchical Deep Multiagent Reinforcement Learning

Despite deep reinforcement learning has recently achieved great successe...

0 Hongyao Tang, et al. ∙

research

∙ 09/12/2018

Bayes-ToMoP: A Fast Detection and Best Response Algorithm Towards Sophisticated Opponents

Multiagent algorithms often aim to accurately predict the behaviors of o...

0 Tianpei Yang, et al. ∙

research

∙ 02/23/2018

Weighted Double Deep Multiagent Reinforcement Learning in Stochastic Cooperative Environments

Despite single agent deep reinforcement learning has achieved significan...

0 Yan Zheng, et al. ∙

research

∙ 01/27/2018

Interactive Deep Colorization With Simultaneous Global and Local Inputs

Colorization methods using deep neural networks have become a recent tre...

0 Yi Xiao, et al. ∙

research

∙ 01/03/2018

Joint convolutional neural pyramid for depth map super-resolution

High-resolution depth map can be inferred from a low-resolution one with...

0 Yi Xiao, et al. ∙

research

∙ 09/13/2017

Visualization of Big Spatial Data using Coresets for Kernel Density Estimates

The size of large, geo-located datasets has reached scales where visuali...

0 Yan Zheng, et al. ∙

Yan Zheng

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