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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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07/16/2023
Magnetic Field-Based Reward Shaping for Goal-Conditioned Reinforcement Learning
Goal-conditioned reinforcement learning (RL) is an interesting extension...
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05/12/2023
Boosting Value Decomposition via Unit-Wise Attentive State Representation for Cooperative Multi-Agent Reinforcement Learning
In cooperative multi-agent reinforcement learning (MARL), the environmen...
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05/09/2023
Attention-Based Transformer Networks for Quantum State Tomography
Neural networks have been actively explored for quantum state tomography...
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04/26/2023
NA^2Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning
Value decomposition is widely used in cooperative multi-agent reinforcem...
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09/15/2022
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees
Multi-agent reinforcement learning (MARL) recently has achieved tremendo...
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07/25/2022
Adaptive Marginalized Semantic Hashing for Unpaired Cross-Modal Retrieval
In recent years, Cross-Modal Hashing (CMH) has aroused much attention du...
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07/16/2022
Model-Aware Contrastive Learning: Towards Escaping Uniformity-Tolerance Dilemma in Training
Instance discrimination contrastive learning (CL) has achieved significa...
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05/22/2022
A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning
While reinforcement learning (RL) algorithms are achieving state-of-the-...
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04/16/2022
Efficient Bayesian Policy Reuse with a Scalable Observation Model in Deep Reinforcement Learning
Bayesian policy reuse (BPR) is a general policy transfer framework for s...
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03/06/2022
Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation
Multi-agent settings remain a fundamental challenge in the reinforcement...
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12/13/2021
Shaping Visual Representations with Attributes for Few-Shot Learning
Few-shot recognition aims to recognize novel categories under low-data r...
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09/27/2021
Sparse Spatial Transformers for Few-Shot Learning
Learning from limited data is a challenging task since the scarcity of d...
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04/15/2021
Rule-Based Reinforcement Learning for Efficient Robot Navigation with Space Reduction
For real-world deployments, it is critical to allow robots to navigate i...
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04/04/2021
Perspective-corrected Spatial Referring Expression Generation for Human-Robot Interaction
Intelligent robots designed to interact with humans in real scenarios ne...
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03/21/2021
Hierarchical Representation based Query-Specific Prototypical Network for Few-Shot Image Classification
Few-shot image classification aims at recognizing unseen categories with...
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03/21/2021
Multi-level Metric Learning for Few-shot Image Recognition
Few-shot learning is devoted to training a model on few samples. Recentl...
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01/06/2021
Deep Reinforcement Learning with Quantum-inspired Experience Replay
In this paper, a novel training paradigm inspired by quantum computation...
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12/31/2020
Curriculum-based Deep Reinforcement Learning for Quantum Control
Deep reinforcement learning has been recognized as an efficient techniqu...
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11/30/2020
Multi-scale Adaptive Task Attention Network for Few-Shot Learning
The goal of few-shot learning is to classify unseen categories with few ...
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10/09/2020
Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments
Evolution strategies (ES), as a family of black-box optimization algorit...
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07/28/2020
Lifelong Incremental Reinforcement Learning with Online Bayesian Inference
A central capability of a long-lived reinforcement learning (RL) agent i...
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05/22/2020
On compression rate of quantum autoencoders: Control design, numerical and experimental realization
Quantum autoencoders which aim at compressing quantum information in a l...
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06/08/2018
Fidelity-based Probabilistic Q-learning for Control of Quantum Systems
The balance between exploration and exploitation is a key problem for re...
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02/13/2017
Differential Evolution for Quantum Robust Control: Algorithm, Applications and Experiments
Robust control design for quantum systems has been recognized as a key t...
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08/21/2015
