Feng Zhou

According to our database, Feng Zhou authored at least 32 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Navigating Towards Fairness with Data Selection.

Yixuan Zhang, Zhidong Li, Yang Wang, Fang Chen, Xuhui Fan, Feng Zhou

CoRR, 2024

Series-to-Series Diffusion Bridge Model.

Hao Yang, Zhanbo Feng, Feng Zhou, Robert C. Qiu, Zenan Ling

CoRR, 2024

IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks.

Junchao Lin, Zenan Ling, Zhanbo Feng, Feng Zhou, Jingwen Xu, Robert C. Qiu

CoRR, 2024

Federated Neural Nonparametric Point Processes.

Hui Chen, Hengyu Liu, Yaqiong Li, Xuhui Fan, Zhilin Zhao, Feng Zhou, Christopher John Quinn, Longbing Cao

CoRR, 2024

Nonstationary Sparse Spectral Permanental Process.

Zicheng Sun, Yixuan Zhang, Zenan Ling, Xuhui Fan, Feng Zhou

CoRR, 2024

Bias Mitigation in Fine-tuning Pre-trained Models for Enhanced Fairness and Efficiency.

Yixuan Zhang, Feng Zhou

CoRR, 2024

Interpretable Transformer Hawkes Processes: Unveiling Complex Interactions in Social Networks.

Zizhuo Meng, Ke Wan, Yadong Huang, Zhidong Li, Yang Wang, Feng Zhou

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures.

Zenan Ling, Longbo Li, Zhanbo Feng, Yixuan Zhang, Feng Zhou, Robert C. Qiu, Zhenyu Liao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes.

Zizhuo Meng, Boyu Li, Xuhui Fan, Zhidong Li, Yang Wang, Fang Chen, Feng Zhou

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Mitigating Label Bias in Machine Learning: Fairness through Confident Learning.

Yixuan Zhang, Boyu Li, Zenan Ling, Feng Zhou

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Heterogeneous multi-task Gaussian Cox processes.

Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu

Mach. Learn., December, 2023

Zero-shot Inversion Process for Image Attribute Editing with Diffusion Models.

Zhanbo Feng, Zenan Ling, Ci Gong, Feng Zhou, Jie Li, Robert C. Qiu

CoRR, 2023

pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints.

Yongli Mou, Jiahui Geng, Feng Zhou, Oya Beyan, Chunming Rong, Stefan Decker

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes.

Yixuan Zhang, Quyu Kong, Feng Zhou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fair Representation Learning with Unreliable Labels.

Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Efficient Inference for Dynamic Flexible Interactions of Neural Populations.

Feng Zhou, Quyu Kong, Zhijie Deng, Jichao Kan, Yixuan Zhang, Cheng Feng, Jun Zhu

J. Mach. Learn. Res., 2022

De-biased Representation Learning for Fairness with Unreliable Labels.

Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen

CoRR, 2022

Deep Ensemble as a Gaussian Process Approximate Posterior.

Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu

CoRR, 2022

Accelerated Linearized Laplace Approximation for Bayesian Deep Learning.

Zhijie Deng, Feng Zhou, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Efficient EM-variational inference for nonparametric Hawkes process.

Feng Zhou, Simon Luo, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

Stat. Comput., 2021

Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer.

Shiye Lei, Zhuozhuo Tu, Leszek Rutkowski, Feng Zhou, Li Shen, Fengxiang He, Dacheng Tao

CoRR, 2021

Nonlinear Hawkes Processes in Time-Varying System.

Feng Zhou, Quyu Kong, Yixuan Zhang, Cheng Feng, Jun Zhu

CoRR, 2021

Continuous-time edge modelling using non-parametric point processes.

Xuhui Fan, Bin Li, Feng Zhou, Scott A. Sisson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Inference of Flexible Interaction in Spiking-neuron Networks.

Feng Zhou, Yixuan Zhang, Jun Zhu

Proceedings of the 9th International Conference on Learning Representations, 2021

Bias-tolerant Fair Classification.

Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Fast multi-resolution segmentation for nonstationary Hawkes process using cumulants.

Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

Int. J. Data Sci. Anal., 2020

Efficient Inference of Nonparametric Interaction in Spiking-neuron Networks.

Feng Zhou, Yixuan Zhang, Jun Zhu

CoRR, 2020

Additive Poisson Process: Learning Intensity of Higher-Order Interaction in Stochastic Processes.

Simon Luo, Feng Zhou, Lamiae Azizi, Mahito Sugiyama

CoRR, 2020

2019

Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation.

Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

CoRR, 2019

Efficient EM-Variational Inference for Hawkes Process.

Feng Zhou

CoRR, 2019

Hawkes Process with Stochastic Triggering Kernel.

Feng Zhou, Yixuan Zhang, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018

A Refined MISD Algorithm Based on Gaussian Process Regression.

Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018