Zeke Xie

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 29

Top Topics

Diffusion Models

Avoid Overfitting

Stochastic Gradient

Top Venues

Publications

Zhongrui Yu, Haoran Wang, Jinze Yang, Hanzhang Wang, Zeke Xie, Yunfeng Cai, Jiale Cao, Zhong Ji, Mingming Sun
SGD: Street View Synthesis with Gaussian Splatting and Diffusion Prior. CoRR (2024)
Xindi Yang, Zeke Xie, Xiong Zhou, Boyu Liu, Buhua Liu, Yi Liu, Haoran Wang, Yunfeng Cai, Mingming Sun
Neural Field Classifiers via Target Encoding and Classification Loss. ICLR (2024)
Jinze Yang, Haoran Wang, Zining Zhu, Chenglong Liu, Meng Wymond Wu, Zeke Xie, Zhong Ji, Jungong Han, Mingming Sun
VIP: Versatile Image Outpainting Empowered by Multimodal Large Language Model. CoRR (2024)
Haoyi Xiong, Zhiyuan Wang, Xuhong Li, Jiang Bian, Zeke Xie, Shahid Mumtaz, Laura E. Barnes
Converging Paradigms: The Synergy of Symbolic and Connectionist AI in LLM-Empowered Autonomous Agents. CoRR (2024)
Xindi Yang, Zeke Xie, Xiong Zhou, Boyu Liu, Buhua Liu, Yi Liu, Haoran Wang, Yunfeng Cai, Mingming Sun
Neural Field Classifiers via Target Encoding and Classification Loss. CoRR (2024)
Zipeng Qi, Lichen Bai, Haoyi Xiong, Zeke Xie
Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization. CoRR (2024)
Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data. ICLR (2024)
Hanzhang Wang, Haoran Wang, Jinze Yang, Zhongrui Yu, Zeke Xie, Lei Tian, Xinyan Xiao, Junjun Jiang, Xianming Liu, Mingming Sun
HiCAST: Highly Customized Arbitrary Style Transfer with Adapter Enhanced Diffusion Models. CoRR (2024)
Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. NeurIPS (2023)
Zeke Xie, Qian-Yuan Tang, Mingming Sun, Ping Li
On the Overlooked Structure of Stochastic Gradients. NeurIPS (2023)
Zeke Xie, Xindi Yang, Yujie Yang, Qi Sun, Yixiang Jiang, Haoran Wang, Yunfeng Cai, Mingming Sun
S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields. ICCV (2023)
Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li
Dataset Pruning: Reducing Training Data by Examining Generalization Influence. ICLR (2023)
Zeke Xie, Xindi Yang, Yujie Yang, Qi Sun, Yixiang Jiang, Haoran Wang, Yunfeng Cai, Mingming Sun
S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields. CoRR (2023)
Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li
Dataset Pruning: Reducing Training Data by Examining Generalization Influence. CoRR (2022)
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum. ICML (2022)
Zheng He, Zeke Xie, Quanzhi Zhu, Zengchang Qin
Sparse Double Descent: Where Network Pruning Aggravates Overfitting. CoRR (2022)
Zeke Xie, Qian-Yuan Tang, Zheng He, Mingming Sun, Ping Li
Rethinking the Structure of Stochastic Gradients: Empirical and Statistical Evidence. CoRR (2022)
Zeke Xie, Qian-Yuan Tang, Yunfeng Cai, Mingming Sun, Ping Li
On the Power-Law Spectrum in Deep Learning: A Bridge to Protein Science. CoRR (2022)
Zheng He, Zeke Xie, Quanzhi Zhu, Zengchang Qin
Sparse Double Descent: Where Network Pruning Aggravates Overfitting. ICML (2022)
Zeke Xie, Issei Sato, Masashi Sugiyama
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima. ICLR (2021)
Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, Masashi Sugiyama
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting. Neural Comput. 33 (8) (2021)
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. ICML (2021)
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. CoRR (2021)
Zeke Xie, Issei Sato, Masashi Sugiyama
A Diffusion Theory for Deep Learning Dynamics: Stochastic Gradient Descent Escapes From Sharp Minima Exponentially Fast. CoRR (2020)
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia. CoRR (2020)
Zeke Xie, Issei Sato, Masashi Sugiyama
Stable Weight Decay Regularization. CoRR (2020)
Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, Masashi Sugiyama
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting. CoRR (2020)
Zeke Xie, Issei Sato
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. CoRR (2017)
Zeke Xie, Issei Sato
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. ACML (2017)