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08/25/2023
A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training
Brain-computer interfaces (BCIs) provide a direct pathway from the brain...
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06/21/2023
Mitigating Communication Costs in Neural Networks: The Role of Dendritic Nonlinearity
Our comprehension of biological neuronal networks has profoundly influen...
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06/19/2023
Controlling Type Confounding in Ad Hoc Teamwork with Instance-wise Teammate Feedback Rectification
Ad hoc teamwork requires an agent to cooperate with unknown teammates wi...
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06/06/2023
ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks
Spiking neural networks (SNNs) have manifested remarkable advantages in ...
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05/20/2023
Prompt ChatGPT In MNER: Improved multimodal named entity recognition method based on auxiliary refining knowledge from ChatGPT
Multimodal Named Entity Recognition (MNER) on social media aims to enhan...
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04/20/2023
NeuSort: An Automatic Adaptive Spike Sorting Approach with Neuromorphic Models
Spike sorting, which classifies spiking events of different neurons from...
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04/19/2023
Biologically inspired structure learning with reverse knowledge distillation for spiking neural networks
Spiking neural networks (SNNs) have superb characteristics in sensory in...
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04/12/2023
Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation
Spiking neural networks (SNNs) are well known as the brain-inspired mode...
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04/11/2023
SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving
Accurate camera-to-lidar calibration is a requirement for sensor data fu...
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10/12/2022
Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks
Spiking neural networks (SNNs) are bio-inspired neural networks with asy...
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07/26/2022
SPAIC: A Spike-based Artificial Intelligence Computing Framework
Neuromorphic computing is an emerging research field that aims to develo...
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05/01/2022
TinyLight: Adaptive Traffic Signal Control on Devices with Extremely Limited Resources
Recent advances in deep reinforcement learning (DRL) have largely promot...
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04/22/2022
Dynamic Ensemble Bayesian Filter for Robust Control of a Human Brain-machine Interface
Objective: Brain-machine interfaces (BMIs) aim to provide direct brain c...
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06/15/2021
Thompson Sampling for Unimodal Bandits
In this paper, we propose a Thompson Sampling algorithm for unimodal ban...
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04/22/2021
Optimize Neural Fictitious Self-Play in Regret Minimization Thinking
Optimization of deep learning algorithms to approach Nash Equilibrium re...
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01/28/2021
Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN
Reconstructing seeing images from fMRI recordings is an absorbing resear...
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12/02/2020
Sample Complexity of Policy Gradient Finding Second-Order Stationary Points
The goal of policy-based reinforcement learning (RL) is to search the ma...
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02/14/2020
Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks
Address event representation (AER) cameras have recently attracted more ...
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11/19/2019
Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons
This paper proposes an unsupervised address event representation (AER) o...
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11/02/2019
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces
Brain-computer interfaces (BCIs) have enabled prosthetic device control ...
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09/06/2019
Gradient Q(σ, λ): A Unified Algorithm with Function Approximation for Reinforcement Learning
Full-sampling (e.g., Q-learning) and pure-expectation (e.g., Expected Sa...
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07/01/2019
FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
In recent years significant progress has been made in dealing with chall...
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06/17/2019
Brain Network Construction and Classification Toolbox (BrainNetClass)
Brain functional network has become an increasingly used approach in und...
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05/17/2019
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
Off-policy reinforcement learning with eligibility traces is challenging...
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03/22/2019
Monte Carlo Neural Fictitious Self-Play: Achieve Approximate Nash equilibrium of Imperfect-Information Games
Researchers on artificial intelligence have achieved human-level intelli...
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03/22/2019
Monte Carlo Neural Fictitious Self-Play: Approach to Approximate Nash equilibrium of Imperfect-Information Games
Researchers on artificial intelligence have achieved human-level intelli...
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02/25/2019
Field-aware Neural Factorization Machine for Click-Through Rate Prediction
Recommendation systems and computing advertisements have gradually enter...
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11/10/2018
Efficient Spiking Neural Networks with Logarithmic Temporal Coding
A Spiking Neural Network (SNN) can be trained indirectly by first traini...
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06/14/2018
Qualitative Measurements of Policy Discrepancy for Return-based Deep Q-Network
In this paper, we focus on policy discrepancy in return-based deep Q-net...
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04/28/2018
Spiking Deep Residual Network
Recently, spiking neural network (SNN) has received significant attentio...
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04/23/2018
State Distribution-aware Sampling for Deep Q-learning
A critical and challenging problem in reinforcement learning is how to l...
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02/09/2018
A Unified Approach for Multi-step Temporal-Difference Learning with Eligibility Traces in Reinforcement Learning
Recently, a new multi-step temporal learning algorithm, called Q(σ), uni...
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04/13/2015
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction
Object detection systems based on the deep convolutional neural network ...
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01/20/2015
Robust Face Recognition by Constrained Part-based Alignment
Developing a reliable and practical face recognition system is a long-st...
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03/06/2014
