Junfeng Wen

Orcid: 0000-0002-4128-1422

According to our database1, Junfeng Wen authored at least 15 papers between 2014 and 2024.

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Bibliography

2024
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models.
CoRR, 2024

An Enhanced Combinatorial Contextual Neural Bandit Approach for Client Selection in Federated Learning.
Proceedings of the European Interdisciplinary Cybersecurity Conference, 2024

2022
Find Your Friends: Personalized Federated Learning with the Right Collaborators.
CoRR, 2022

A Parametric Class of Approximate Gradient Updates for Policy Optimization.
Proceedings of the International Conference on Machine Learning, 2022

2021
ProxyFL: Decentralized Federated Learning through Proxy Model Sharing.
CoRR, 2021

Characterizing the Gap Between Actor-Critic and Policy Gradient.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Universal Successor Features for Transfer Reinforcement Learning.
CoRR, 2020

Domain Aggregation Networks for Multi-Source Domain Adaptation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Batch Stationary Distribution Estimation.
Proceedings of the 37th International Conference on Machine Learning, 2020

2018
Few-Shot Self Reminder to Overcome Catastrophic Forgetting.
CoRR, 2018

Universal Successor Representations for Transfer Reinforcement Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

2016
Convex Two-Layer Modeling with Latent Structure.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Correcting Covariate Shift with the Frank-Wolfe Algorithm.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Optimal Estimation of Multivariate ARMA Models.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification.
Proceedings of the 31th International Conference on Machine Learning, 2014


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