Yikai Zhang

According to our database, Yikai Zhang authored at least 21 papers between 2019 and 2024.

Collaborative distances:

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

2024

Learning to Abstain From Uninformative Data.

Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen

Trans. Mach. Learn. Res., 2024

OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI.

Zhen Huang, Zengzhi Wang, Shijie Xia, Xuefeng Li, Haoyang Zou, Ruijie Xu, Run-Ze Fan, Lyumanshan Ye, Ethan Chern, Yixin Ye, Yikai Zhang, Yuqing Yang, Ting Wu, Binjie Wang, Shichao Sun, Yang Xiao, Yiyuan Li, Fan Zhou, Steffi Chern, Yiwei Qin, Yan Ma, Jiadi Su, Yixiu Liu, Yuxiang Zheng, Shaoting Zhang, Dahua Lin, Yu Qiao, Pengfei Liu

CoRR, 2024

Extending LLMs' Context Window with 100 Samples.

Yikai Zhang, Junlong Li, Pengfei Liu

CoRR, 2024

Dissecting Human and LLM Preferences.

Junlong Li, Fan Zhou, Shichao Sun, Yikai Zhang, Hai Zhao, Pengfei Liu

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Manifold-driven decomposition for adversarial robustness.

Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Yi Yao, Mayank Goswami, Chao Chen, Dimitris N. Metaxas

Frontiers Comput. Sci., 2023

Topology-Aware Uncertainty for Image Segmentation.

Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen

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

Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation.

Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka

Proceedings of the International Conference on Machine Learning, 2023

Learning to Segment from Noisy Annotations: A Spatial Correction Approach.

Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Risk Bounds on Aleatoric Uncertainty Recovery.

Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka

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

2022

On the Convergence of Optimizing Persistent-Homology-Based Losses.

Yikai Zhang, Jiachen Yao, Yusu Wang, Chao Chen

CoRR, 2022

A Manifold View of Adversarial Risk.

Wenjia Zhang, Yikai Zhang, Xiaolin Hu, Mayank Goswami, Chao Chen, Dimitris N. Metaxas

CoRR, 2022

Stability of SGD: Tightness analysis and improved bounds.

Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami

Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Manifold View of Adversarial Risk.

Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Mayank Goswami, Chao Chen, Dimitris N. Metaxas

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

2021

Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach.

Yikai Zhang, Hui Qu, Qi Chang, Huidong Liu, Dimitris N. Metaxas, Chao Chen

CoRR, 2021

Topological Detection of Trojaned Neural Networks.

Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen

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

Learning with Feature-Dependent Label Noise: A Progressive Approach.

Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen

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

2020

Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information.

Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu, Yikai Zhang, Tong Zhang, Shaoting Zhang, Dimitris N. Metaxas

CoRR, 2020

Learn Distributed GAN with Temporary Discriminators.

Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris N. Metaxas

Proceedings of the Computer Vision - ECCV 2020, 2020

Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data.

Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Local Regularizer Improves Generalization.

Yikai Zhang, Hui Qu, Dimitris N. Metaxas, Chao Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Taming the Noisy Gradient: Train Deep Neural Networks with Small Batch Sizes.

Yikai Zhang, Hui Qu, Chao Chen, Dimitris N. Metaxas

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019