b'Jianye Hao'

research

∙ 08/07/2023

Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

Graph Neural Network (GNN)-based models have become the mainstream appro...

0 Taichi Liu, 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

∙ 07/14/2023

Exploiting Counter-Examples for Active Learning with Partial labels

This paper studies a new problem, active learning with partial labels (A...

0 Fei Zhang, et al. ∙

research

∙ 07/03/2023

VOLTA: Diverse and Controllable Question-Answer Pair Generation with Variational Mutual Information Maximizing Autoencoder

Previous question-answer pair generation methods aimed to produce fluent...

0 Yueen Ma, 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

∙ 05/02/2023

Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems

Recommender systems now consume large-scale data and play a significant ...

0 Yuening Wang, et al. ∙

research

∙ 03/12/2023

Traj-MAE: Masked Autoencoders for Trajectory Prediction

Trajectory prediction has been a crucial task in building a reliable aut...

0 Hao Chen, et al. ∙

research

∙ 03/09/2023

Out-of-distribution Detection with Implicit Outlier Transformation

Outlier exposure (OE) is powerful in out-of-distribution (OOD) detection...

0 Qizhou Wang, et al. ∙

research

∙ 03/06/2023

DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction

Attaining the equilibrium state of a catalyst-adsorbate system is key to...

0 Bowen Wang, et al. ∙

research

∙ 03/02/2023

The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting

Knowing the learning dynamics of policy is significant to unveiling the ...

0 Hongyao Tang, et al. ∙

research

∙ 02/06/2023

Spectral Augmentations for Graph Contrastive Learning

Contrastive learning has emerged as a premier method for learning repres...

0 Amur Ghose, et al. ∙

research

∙ 01/30/2023

Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization

We proposed a new technique to accelerate sampling methods for solving d...

0 Junlong Lyu, et al. ∙

research

∙ 12/30/2022

Transformer in Transformer as Backbone for Deep Reinforcement Learning

Designing better deep networks and better reinforcement learning (RL) al...

0 Hangyu Mao, et al. ∙

research

∙ 12/29/2022

Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network

The mobile communication enabled by cellular networks is the one of the ...

0 Mehrtash Mehrabi, et al. ∙

research

∙ 12/18/2022

Planning Immediate Landmarks of Targets for Model-Free Skill Transfer across Agents

In reinforcement learning applications like robotics, agents usually nee...

0 Minghuan Liu, et al. ∙

research

∙ 11/23/2022

Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning

The latent world model provides a promising way to learn policies in a c...

0 Junjie Wang, et al. ∙

research

∙ 11/07/2022

RITA: Boost Autonomous Driving Simulators with Realistic Interactive Traffic Flow

High-quality traffic flow generation is the core module in building simu...

0 Zhengbang Zhu, 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

∙ 10/17/2022

PTDE: Personalized Training with Distillated Execution for Multi-Agent Reinforcement Learning

Centralized Training with Decentralized Execution (CTDE) has been a very...

0 Yiqun Chen, et al. ∙

research

∙ 10/09/2022

Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning

Adapting to the changes in transition dynamics is essential in robotic a...

0 Yao Mu, 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

∙ 07/26/2022

Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning

Deriving a good variable selection strategy in branch-and-bound is essen...

4 Zeren Huang, et al. ∙

research

∙ 06/17/2022

A Graph-Enhanced Click Model for Web Search

To better exploit search logs and model users' behavior patterns, numero...

0 Jianghao Lin, et al. ∙

research

∙ 05/27/2022

Off-Beat Multi-Agent Reinforcement Learning

We investigate model-free multi-agent reinforcement learning (MARL) in e...

4 Wei Qiu, et al. ∙

research

∙ 04/19/2022

A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets

In recent years, interest has arisen in using machine learning to improv...

16 Wei Chen, 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

∙ 03/24/2022

LHNN: Lattice Hypergraph Neural Network for VLSI Congestion Prediction

Precise congestion prediction from a placement solution plays a crucial ...

0 Bowen Wang, 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

∙ 03/16/2022

Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents

Multi-agent reinforcement learning is difficult to be applied in practic...

3 Jian Zhao, et al. ∙

research

∙ 03/04/2022

Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization

Recent progress in state-only imitation learning extends the scope of ap...

1 Minghuan Liu, et al. ∙

research

∙ 02/09/2022

Revisiting QMIX: Discriminative Credit Assignment by Gradient Entropy Regularization

In cooperative multi-agent systems, agents jointly take actions and rece...

11 Jian Zhao, 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

∙ 11/24/2021

Learning State Representations via Retracing in Reinforcement Learning

We propose learning via retracing, a novel self-supervised approach for ...

4 Changmin Yu, 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

∙ 11/17/2021

SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

The MineRL competition is designed for the development of reinforcement ...

12 Hangyu Mao, et al. ∙

research

∙ 10/20/2021

Dynamic Bottleneck for Robust Self-Supervised Exploration

Exploration methods based on pseudo-count of transitions or curiosity of...

9 Chenjia Bai, et al. ∙

research

∙ 10/09/2021

Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning

The backpropagation networks are notably susceptible to catastrophic for...

0 Danruo Deng, et al. ∙

research

∙ 10/08/2021

Ranking Cost: Building An Efficient and Scalable Circuit Routing Planner with Evolution-Based Optimization

Circuit routing has been a historically challenging problem in designing...

0 Shiyu Huang, et al. ∙

research

∙ 09/14/2021

Exploration in Deep Reinforcement Learning: A Comprehensive Survey

Deep Reinforcement Learning (DRL) and Deep Multi-agent Reinforcement Lea...

10 Tianpei Yang, 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

∙ 06/02/2021

Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms

Domain generalization aims to learn knowledge invariant across different...

0 Yunqi Wang, et al. ∙

research

∙ 06/01/2021

Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment

Extending transfer learning to cooperative multi-agent reinforcement lea...

0 Tianze Zhou, et al. ∙

research

∙ 05/28/2021

Learning to Select Cuts for Efficient Mixed-Integer Programming

Cutting plane methods play a significant role in modern solvers for tack...

8 Zeren Huang, et al. ∙

research

∙ 05/14/2021

Ordering-Based Causal Discovery with Reinforcement Learning

It is a long-standing question to discover causal relations among a set ...

4 Xiaoqiang Wang, et al. ∙

research

∙ 05/13/2021

Principled Exploration via Optimistic Bootstrapping and Backward Induction

One principled approach for provably efficient exploration is incorporat...

3 Chenjia Bai, et al. ∙

research

∙ 04/13/2021

An Adversarial Imitation Click Model for Information Retrieval

Modern information retrieval systems, including web search, ads placemen...

0 Xinyi Dai, et al. ∙

research

∙ 03/15/2021

Learning Symbolic Rules for Interpretable Deep Reinforcement Learning

Recent progress in deep reinforcement learning (DRL) can be largely attr...

14 Zhihao Ma, et al. ∙

research

∙ 11/13/2020

Critic PI2: Master Continuous Planning via Policy Improvement with Path Integrals and Deep Actor-Critic Reinforcement Learning

Constructing agents with planning capabilities has long been one of the ...

0 Jiajun Fan, et al. ∙

research

∙ 10/10/2020

Event-Triggered Multi-agent Reinforcement Learning with Communication under Limited-bandwidth Constraint

Communicating with each other in a distributed manner and behaving as a ...

0 Guangzheng Hu, et al. ∙

Jianye Hao

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