Zixiang Chen

According to our database, Zixiang Chen authored at least 46 papers between 2013 and 2024.

Collaborative distances:

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

2024

LCRNet: local cross-channel recalibration network for liver cancer classification based on CT images.

Qiang Fang, Yue Yang, Hao Wang, Hanxi Sun, Jiangming Chen, Zixiang Chen, Tian Pu, Xiaoqing Zhang, Fubao Liu

Health Inf. Sci. Syst., December, 2024

Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis.

Zikun Zhang, Zixiang Chen, Quanquan Gu

CoRR, 2024

Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent.

Yiwen Kou, Zixiang Chen, Quanquan Gu, Sham M. Kakade

CoRR, 2024

Guided Discrete Diffusion for Electronic Health Record Generation.

Zixiang Chen, Jun Han, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu

CoRR, 2024

Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation.

Huizhuo Yuan, Zixiang Chen, Kaixuan Ji, Quanquan Gu

CoRR, 2024

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.

Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, Quanquan Gu

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

How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP.

Zixiang Chen, Yihe Deng, Yuanzhi Li, Quanquan Gu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Low-dose dynamic cerebral perfusion CT reconstruction based on voxel-level TAC correction (VTC).

Zixiang Chen, Na Zhang, Qiyang Zhang, Kaiyi Liang, Zhenxing Huang, Guotao Quan, Xiang Li, Dong Liang, Zhanli Hu

Biomed. Signal Process. Control., September, 2023

Fast Sampling via De-randomization for Discrete Diffusion Models.

Zixiang Chen, Huizhuo Yuan, Yongqian Li, Yiwen Kou, Junkai Zhang, Quanquan Gu

CoRR, 2023

Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves.

Yihe Deng, Weitong Zhang, Zixiang Chen, Quanquan Gu

CoRR, 2023

Benign Overfitting for Two-layer ReLU Networks.

Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu

CoRR, 2023

Learning High-Dimensional Single-Neuron ReLU Networks with Finite Samples.

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

CoRR, 2023

Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data.

Yiwen Kou, Zixiang Chen, Quanquan Gu

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

Why Does Sharpness-Aware Minimization Generalize Better Than SGD?

Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu

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

Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron.

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

Proceedings of the International Conference on Machine Learning, 2023

Benign Overfitting in Two-layer ReLU Convolutional Neural Networks.

Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu

Proceedings of the International Conference on Machine Learning, 2023

Understanding Train-Validation Split in Meta-Learning with Neural Networks.

Xinzhe Zuo, Zixiang Chen, Huaxiu Yao, Yuan Cao, Quanquan Gu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study.

Yiwen Kou, Zixiang Chen, Yuan Cao, Quanquan Gu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning.

Zixiang Chen, Chris Junchi Li, Huizhuo Yuan, Quanquan Gu, Michael I. Jordan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

High Temporal Resolution Total-Body Dynamic PET Imaging Based on Pixel-Level Time-Activity Curve Correction.

Zixiang Chen, Yaping Wu, Na Zhang, Tao Sun, Yu Shen, Hairong Zheng, Dong Liang, Meiyun Wang, Zhanli Hu

IEEE Trans. Biomed. Eng., 2022

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning.

Zixiang Chen, Chris Junchi Li, Angela Yuan, Quanquan Gu, Michael I. Jordan

CoRR, 2022

Towards Understanding Mixture of Experts in Deep Learning.

Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li

CoRR, 2022

Benign Overfitting in Two-layer Convolutional Neural Networks.

Yuan Cao, Zixiang Chen, Mikhail Belkin, Quanquan Gu

CoRR, 2022

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation.

Zhengyong Huang, Sijuan Zou, Guoshuai Wang, Zixiang Chen, Hao Shen, Haiyan Wang, Na Zhang, Lu Zhang, Fan Yang, Haining Wang, Dong Liang, Tianye Niu, Xiaohua Zhu, Zhanli Hu

Comput. Methods Programs Biomed., 2022

TG-Net: Combining transformer and GAN for nasopharyngeal carcinoma tumor segmentation based on total-body uEXPLORER PET/CT scanner.

Zhengyong Huang, Si Tang, Zixiang Chen, Guoshuai Wang, Hao Shen, Yun Zhou, Haining Wang, Wei Fan, Dong Liang, Yingying Hu, Zhanli Hu

Comput. Biol. Medicine, 2022

Towards Understanding the Mixture-of-Experts Layer in Deep Learning.

Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li

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

Benign Overfitting in Two-layer Convolutional Neural Networks.

Yuan Cao, Zixiang Chen, Misha Belkin, Quanquan Gu

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

Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games.

Zixiang Chen, Dongruo Zhou, Quanquan Gu

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Faster Perturbed Stochastic Gradient Methods for Finding Local Minima.

Zixiang Chen, Dongruo Zhou, Quanquan Gu

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Self-training Converts Weak Learners to Strong Learners in Mixture Models.

Spencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites.

Zhenxing Huang, Xinfeng Liu, Rongpin Wang, Zixiang Chen, Yongfeng Yang, Xin Liu, Hairong Zheng, Dong Liang, Zhanli Hu

IEEE J. Biomed. Health Informatics, 2021

Factored heterogeneous similarity model for recommendation with implicit feedback.

Yongxin Ni, Xiancong Chen, Weike Pan, Zixiang Chen, Zhong Ming

Neurocomputing, 2021

Dynamic PET Imaging Using Dual Texture Features.

Zhanglei Ouyang, Shujun Zhao, Zhaoping Cheng, Yanhua Duan, Zixiang Chen, Na Zhang, Dong Liang, Zhanli Hu

Frontiers Comput. Neurosci., 2021

Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation.

Zixiang Chen, Dongruo Zhou, Quanquan Gu

CoRR, 2021

How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?

Zixiang Chen, Yuan Cao, Difan Zou, Quanquan Gu

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

2020

CaGAN: A Cycle-Consistent Generative Adversarial Network With Attention for Low-Dose CT Imaging.

Zhiyuan Huang, Zixiang Chen, Qiyang Zhang, Guotao Quan, Min Ji, Chengjin Zhang, Yongfeng Yang, Xin Liu, Dong Liang, Hairong Zheng, Zhanli Hu

IEEE Trans. Computational Imaging, 2020

Matrix factorization with heterogeneous multiclass preference context.

Jing Lin, Weike Pan, Lin Li, Zixiang Chen, Zhong Ming

Neurocomputing, 2020

Conditional restricted Boltzmann machine for item recommendation.

Zixiang Chen, Wanqi Ma, Wei Dai, Weike Pan, Zhong Ming

Neurocomputing, 2020

<i>k</i>-Reciprocal nearest neighbors algorithm for one-class collaborative filtering.

Wei Cai, Weike Pan, Jixiong Liu, Zixiang Chen, Zhong Ming

Neurocomputing, 2020

Mean-Field Analysis of Two-Layer Neural Networks: Non-Asymptotic Rates and Generalization Bounds.

Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang

CoRR, 2020

A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks.

Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

Stein Neural Sampler.

Tianyang Hu, Zixiang Chen, Hanxi Sun, Jincheng Bai, Mao Ye, Guang Cheng

CoRR, 2018

2017

k-CoFi: Modeling k-Granularity Preference Context in Collaborative Filtering.

Yunfeng Huang, Zixiang Chen, Lin Li, Weike Pan, Zhiguang Shan, Zhong Ming

Proceedings of the Smart Computing and Communication, 2017

2014

Hybrid biogeography-based evolutionary algorithms.

Haiping Ma, Dan Simon, Minrui Fei, Xinzhan Shu, Zixiang Chen

Eng. Appl. Artif. Intell., 2014

2013

On the equivalences and differences of evolutionary algorithms.

Haiping Ma, Dan Simon, Minrui Fei, Zixiang Chen

Eng. Appl. Artif. Intell., 2013