Search Results for author: Mengzhu Wang

Found 7 papers, 0 papers with code

Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?

no code implementations20 May 2024 Yang Dai, Oubo Ma, Longfei Zhang, Xingxing Liang, Shengchao Hu, Mengzhu Wang, Shouling Ji, Jincai Huang, Li Shen

Transformer-based trajectory optimization methods have demonstrated exceptional performance in offline Reinforcement Learning (offline RL), yet it poses challenges due to substantial parameter size and limited scalability, which is particularly critical in sequential decision-making scenarios where resources are constrained such as in robots and drones with limited computational power.

Atari Games Offline RL +1

Dynamic Spiking Graph Neural Networks

no code implementations15 Dec 2023 Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Bin Gu, Huan Xiong

Current work often uses SNNs instead of Recurrent Neural Networks (RNNs) by using binary features instead of continuous ones for efficient training, which would overlooks graph structure information and leads to the loss of details during propagation.

Dynamic Node Classification Graph Representation Learning

Singular Value Penalization and Semantic Data Augmentation for Fully Test-Time Adaptation

no code implementations10 Dec 2023 Houcheng Su, Daixian Liu, Mengzhu Wang, Wei Wang

Recent domain adaptation study has shown that maximizing the sum of singular values of prediction results can simultaneously enhance their confidence (discriminability) and diversity.

Data Augmentation Test-time Adaptation

CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification

no code implementations8 Jun 2023 Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo

Although graph neural networks (GNNs) have achieved impressive achievements in graph classification, they often need abundant task-specific labels, which could be extensively costly to acquire.

Contrastive Learning Domain Adaptation +2

Semantic Data Augmentation based Distance Metric Learning for Domain Generalization

no code implementations2 Aug 2022 Mengzhu Wang, Jianlong Yuan, Qi Qian, Zhibin Wang, Hao Li

Further, we provide an in-depth analysis of the mechanism and rational behind our approach, which gives us a better understanding of why leverage logits in lieu of features can help domain generalization.

Data Augmentation Domain Generalization +1

On the Equity of Nuclear Norm Maximization in Unsupervised Domain Adaptation

no code implementations12 Apr 2022 Wenju Zhang, Xiang Zhang, Qing Liao, Long Lan, Mengzhu Wang, Wei Wang, Baoyun Peng, Zhengming Ding

Nuclear norm maximization has shown the power to enhance the transferability of unsupervised domain adaptation model (UDA) in an empirical scheme.

Image Classification Unsupervised Domain Adaptation

Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature Redundancy

no code implementations28 Dec 2020 Mengzhu Wang, Xiang Zhang, Long Lan, Wei Wang, Huibin Tan, Zhigang Luo

In this paper, we emphasize the significance of reducing feature redundancy for improving UDA in a bi-level way.

Unsupervised Domain Adaptation

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