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2020 – today
- 2025
[i26]Zeke Xie, Zheng He, Nan Lu, Lichen Bai, Bao Li, Shuo Yang, Mingming Sun, Ping Li:
Learning from Ambiguous Data with Hard Labels. CoRR abs/2501.01844 (2025)- 2024
- [c11]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 - [c10]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 - [i25]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 abs/2401.05870 (2024) - [i24]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 abs/2403.01058 (2024) - [i23]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 abs/2403.20079 (2024) - [i22]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 abs/2406.01059 (2024) - [i21]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 abs/2407.08516 (2024) - [i20]Zipeng Qi, Lichen Bai, Haoyi Xiong, Zeke Xie:
Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization. CoRR abs/2407.14041 (2024) - [i19]Muyao Wang, Zeke Xie, Bo Chen:
Channel-wise Influence: Estimating Data Influence for Multivariate Time Series. CoRR abs/2408.14763 (2024) - [i18]Buhua Liu, Shitong Shao, Bao Li, Lichen Bai, Zhiqiang Xu, Haoyi Xiong, James Kwok, Sumi Helal, Zeke Xie:
Alignment of Diffusion Models: Fundamentals, Challenges, and Future. CoRR abs/2409.07253 (2024) - [i17]Shitong Shao, Zikai Zhou, Lichen Bai, Haoyi Xiong, Zeke Xie:
IV-Mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis. CoRR abs/2410.04171 (2024) - [i16]Tianhao Peng, Yuchen Li, Xuhong Li, Jiang Bian, Zeke Xie, Ning Sui, Shahid Mumtaz, Yanwu Xu, Linghe Kong, Haoyi Xiong:
Pre-trained Molecular Language Models with Random Functional Group Masking. CoRR abs/2411.01401 (2024) - [i15]Zikai Zhou, Shitong Shao, Lichen Bai, Zhiqiang Xu, Bo Han, Zeke Xie:
Golden Noise for Diffusion Models: A Learning Framework. CoRR abs/2411.09502 (2024) - [i14]Shitong Shao, Zikai Zhou, Tian Ye, Lichen Bai, Zhiqiang Xu, Zeke Xie:
Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer. CoRR abs/2411.10781 (2024) - [i13]Lichen Bai, Shitong Shao, Zikai Zhou, Zipeng Qi, Zhiqiang Xu, Haoyi Xiong, Zeke Xie:
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection. CoRR abs/2412.10891 (2024) - [i12]Zipeng Qi, Buhua Liu, Shiyan Zhang, Bao Li, Zhiqiang Xu, Haoyi Xiong, Zeke Xie:
A Simple and Efficient Baseline for Zero-Shot Generative Classification. CoRR abs/2412.12594 (2024) - 2023
- [c9]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: 17978-17988 - [c8]Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li:
Dataset Pruning: Reducing Training Data by Examining Generalization Influence. ICLR 2023 - [c7]Zeke Xie, Qian-Yuan Tang, Mingming Sun, Ping Li:
On the Overlooked Structure of Stochastic Gradients. NeurIPS 2023 - [c6]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 - [i11]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 abs/2308.07032 (2023) - 2022
- [c5]Zheng He, Zeke Xie, Quanzhi Zhu, Zengchang Qin:
Sparse Double Descent: Where Network Pruning Aggravates Overfitting. ICML 2022: 8635-8659 - [c4]Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama:
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum. ICML 2022: 24430-24459 - [i10]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 abs/2201.13011 (2022) - [i9]Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li:
Dataset Pruning: Reducing Training Data by Examining Generalization Influence. CoRR abs/2205.09329 (2022) - [i8]Zheng He, Zeke Xie, Quanzhi Zhu, Zengchang Qin:
Sparse Double Descent: Where Network Pruning Aggravates Overfitting. CoRR abs/2206.08684 (2022) - [i7]Zeke Xie, Qian-Yuan Tang, Zheng He, Mingming Sun, Ping Li:
Rethinking the Structure of Stochastic Gradients: Empirical and Statistical Evidence. CoRR abs/2212.02083 (2022) - 2021
- [j1]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): 2163-2192 (2021) - [c3]Zeke Xie, Issei Sato, Masashi Sugiyama:
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima. ICLR 2021 - [c2]Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama:
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. ICML 2021: 11448-11458 - [i6]Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama:
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. CoRR abs/2103.17182 (2021) - 2020
- [i5]Zeke Xie, Issei Sato, Masashi Sugiyama:
A Diffusion Theory for Deep Learning Dynamics: Stochastic Gradient Descent Escapes From Sharp Minima Exponentially Fast. CoRR abs/2002.03495 (2020) - [i4]Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama:
Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia. CoRR abs/2006.15815 (2020) - [i3]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 abs/2011.06220 (2020) - [i2]Zeke Xie, Issei Sato, Masashi Sugiyama:
Stable Weight Decay Regularization. CoRR abs/2011.11152 (2020)
2010 – 2019
- 2017
- [c1]Zeke Xie, Issei Sato:
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. ACML 2017: 81-96 - [i1]Zeke Xie, Issei Sato:
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. CoRR abs/1711.08117 (2017)
Coauthor Index
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last updated on 2025-02-20 20:43 CET by the dblp team
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