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08/23/2023
Aligning Language Models with Offline Reinforcement Learning from Human Feedback
Learning from human preferences is crucial for language models (LMs) to ...
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07/18/2023
Pixel-wise Graph Attention Networks for Person Re-identification
Graph convolutional networks (GCN) is widely used to handle irregular da...
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07/01/2023
SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency
Extensive studies have shown that deep learning models are vulnerable to...
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06/02/2022
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling
Domain adaptation (DA) aims to transfer knowledge learned from a labeled...
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05/23/2022
Feature-Distribution Perturbation and Calibration for Generalized Person ReID
Person Re-identification (ReID) has been advanced remarkably over the la...
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11/26/2021
Semi-supervised t-SNE for Millimeter-wave Wireless Localization
We consider the mobile localization problem in future millimeter-wave wi...
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09/18/2021
Self-Adaptive Partial Domain Adaptation
Partial Domain adaptation (PDA) aims to solve a more practical cross-dom...
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09/12/2021
An Unsupervised Deep-Learning Method for Fingerprint Classification: the CCAE Network and the Hybrid Clustering Strategy
The fingerprint classification is an important and effective method to q...
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06/27/2021
Policy Perturbation via Noisy Advantage Values for Cooperative Multi-agent Actor-Critic methods
Recent works have applied the Proximal Policy Optimization (PPO) to the ...
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06/26/2021
Domain Adaptive YOLO for One-Stage Cross-Domain Detection
Domain shift is a major challenge for object detectors to generalize wel...
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02/06/2021
RIIT: Rethinking the Importance of Implementation Tricks in Multi-Agent Reinforcement Learning
In recent years, Multi-Agent Reinforcement Learning (MARL) has revolutio...
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09/09/2020
QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning
In Cooperative Multi-Agent Reinforcement Learning (MARL) and under the s...
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01/21/2020
A hybrid model based on deep LSTM for predicting high-dimensional chaotic systems
We propose a hybrid method combining the deep long short-term memory (LS...
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10/15/2018
