Search Results for author: Yanhui Geng

Found 8 papers, 2 papers with code

Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief

3 code implementations13 Oct 2022 Kaiyang Guo, Yunfeng Shao, Yanhui Geng

To make practical, we further devise an offline RL algorithm to approximately find the solution.

D4RL Offline RL +2

Universality of parametric Coupling Flows over parametric diffeomorphisms

no code implementations7 Feb 2022 Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen

Invertible neural networks based on Coupling Flows CFlows) have various applications such as image synthesis and data compression.

Bayesian Optimization Data Compression +1

Structured Directional Pruning via Perturbation Orthogonal Projection

no code implementations12 Jul 2021 Yinchuan Li, Xiaofeng Liu, Yunfeng Shao, Qing Wang, Yanhui Geng

Structured pruning is an effective compression technique to reduce the computation of neural networks, which is usually achieved by adding perturbations to reduce network parameters at the cost of slightly increasing training loss.

Sparse Personalized Federated Learning

no code implementations12 Jul 2021 Xiaofeng Liu, Yinchuan Li, Qing Wang, Xu Zhang, Yunfeng Shao, Yanhui Geng

By incorporating an approximated L1-norm and the correlation between client models and global model into standard FL loss function, the performance on statistical diversity data is improved and the communicational and computational loads required in the network are reduced compared with non-sparse FL.

Personalized Federated Learning

A Causal Direction Test for Heterogeneous Populations

no code implementations8 Jun 2020 Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng

Our simulation result show that the proposed adjustment significantly improves the performance of the causal direction test statistic for heterogeneous data.

Clustering Decision Making +1

Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models

1 code implementation NeurIPS 2018 Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng

The inference of the causal relationship between a pair of observed variables is a fundamental problem in science, and most existing approaches are based on one single causal model.

Causal Inference Clustering

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