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Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN
Reconstructing seeing images from fMRI recordings is an absorbing resear...
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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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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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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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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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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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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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Brain Network Construction and Classification Toolbox (BrainNetClass)
Brain functional network has become an increasingly used approach in und...
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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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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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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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Field-aware Neural Factorization Machine for Click-Through Rate Prediction
Recommendation systems and computing advertisements have gradually enter...
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Efficient Spiking Neural Networks with Logarithmic Temporal Coding
A Spiking Neural Network (SNN) can be trained indirectly by first traini...
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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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Spiking Deep Residual Network
Recently, spiking neural network (SNN) has received significant attentio...
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State Distribution-aware Sampling for Deep Q-learning
A critical and challenging problem in reinforcement learning is how to l...
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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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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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Robust Face Recognition by Constrained Part-based Alignment
Developing a reliable and practical face recognition system is a long-st...
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Sparse Principal Component Analysis via Rotation and Truncation
Sparse principal component analysis (sparse PCA) aims at finding a spars...
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