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08/07/2023
Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation
Graph Neural Network (GNN)-based models have become the mainstream appro...
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08/01/2023
BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization
Evolutionary reinforcement learning (ERL) algorithms recently raise atte...
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07/14/2023
Exploiting Counter-Examples for Active Learning with Partial labels
This paper studies a new problem, active learning with partial labels (A...
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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...
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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 ...
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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 ...
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03/12/2023
Traj-MAE: Masked Autoencoders for Trajectory Prediction
Trajectory prediction has been a crucial task in building a reliable aut...
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03/09/2023
Out-of-distribution Detection with Implicit Outlier Transformation
Outlier exposure (OE) is powerful in out-of-distribution (OOD) detection...
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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...
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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 ...
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02/06/2023
Spectral Augmentations for Graph Contrastive Learning
Contrastive learning has emerged as a premier method for learning repres...
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01/30/2023
Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization
We proposed a new technique to accelerate sampling methods for solving d...
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12/30/2022
Transformer in Transformer as Backbone for Deep Reinforcement Learning
Designing better deep networks and better reinforcement learning (RL) al...
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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 ...
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12/18/2022
Planning Immediate Landmarks of Targets for Model-Free Skill Transfer across Agents
In reinforcement learning applications like robotics, agents usually nee...
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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...
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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...
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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...
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10/17/2022
PTDE: Personalized Training with Distillated Execution for Multi-Agent Reinforcement Learning
Centralized Training with Decentralized Execution (CTDE) has been a very...
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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...
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10/02/2022
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
Unsupervised reinforcement learning (URL) poses a promising paradigm to ...
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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...
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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...
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06/17/2022
A Graph-Enhanced Click Model for Web Search
To better exploit search logs and model users' behavior patterns, numero...
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05/27/2022
Off-Beat Multi-Agent Reinforcement Learning
We investigate model-free multi-agent reinforcement learning (MARL) in e...
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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...
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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 ...
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03/24/2022
LHNN: Lattice Hypergraph Neural Network for VLSI Congestion Prediction
Precise congestion prediction from a placement solution plays a crucial ...
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03/16/2022
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Learning to collaborate is critical in Multi-Agent Reinforcement Learnin...
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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...
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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...
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02/09/2022
Revisiting QMIX: Discriminative Credit Assignment by Gradient Entropy Regularization
In cooperative multi-agent systems, agents jointly take actions and rece...
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12/06/2021
ED2: An Environment Dynamics Decomposition Framework for World Model Construction
Model-based reinforcement learning methods achieve significant sample ef...
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11/24/2021
Learning State Representations via Retracing in Reinforcement Learning
We propose learning via retracing, a novel self-supervised approach for ...
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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...
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11/17/2021
SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
The MineRL competition is designed for the development of reinforcement ...
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10/20/2021
Dynamic Bottleneck for Robust Self-Supervised Exploration
Exploration methods based on pseudo-count of transitions or curiosity of...
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10/09/2021
Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
The backpropagation networks are notably susceptible to catastrophic for...
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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...
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09/14/2021
Exploration in Deep Reinforcement Learning: A Comprehensive Survey
Deep Reinforcement Learning (DRL) and Deep Multi-agent Reinforcement Lea...
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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...
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06/02/2021
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms
Domain generalization aims to learn knowledge invariant across different...
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06/01/2021
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
Extending transfer learning to cooperative multi-agent reinforcement lea...
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05/28/2021
Learning to Select Cuts for Efficient Mixed-Integer Programming
Cutting plane methods play a significant role in modern solvers for tack...
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05/14/2021
Ordering-Based Causal Discovery with Reinforcement Learning
It is a long-standing question to discover causal relations among a set ...
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05/13/2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction
One principled approach for provably efficient exploration is incorporat...
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04/13/2021
An Adversarial Imitation Click Model for Information Retrieval
Modern information retrieval systems, including web search, ads placemen...
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03/15/2021
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning
Recent progress in deep reinforcement learning (DRL) can be largely attr...
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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 ...
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10/10/2020