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Yikai Zhang 0003
Person information
- affiliation: Morgan Stanley, Machine Learning Research, New York, NY, USA
- affiliation: Rutgers University, Department of Computer Science, Piscataway, NJ, USA
Other persons with the same name
- Yikai Zhang — disambiguation page
- Yikai Zhang 0001 — The Chinese University of Hong Kong, Hong Kong
- Yikai Zhang 0002 — Northeastern University, Shenyang, China
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2020 – today
- 2024
- [j2]Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen:
Learning to Abstain From Uninformative Data. Trans. Mach. Learn. Res. 2024 (2024) - [c13]Junlong Li, Fan Zhou, Shichao Sun, Yikai Zhang, Hai Zhao, Pengfei Liu:
Dissecting Human and LLM Preferences. ACL (1) 2024: 1790-1811 - [i16]Yikai Zhang, Junlong Li, Pengfei Liu:
Extending LLMs' Context Window with 100 Samples. CoRR abs/2401.07004 (2024) - [i15]Junlong Li, Fan Zhou, Shichao Sun, Yikai Zhang, Hai Zhao, Pengfei Liu:
Dissecting Human and LLM Preferences. CoRR abs/2402.11296 (2024) - [i14]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:
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI. CoRR abs/2406.12753 (2024) - 2023
- [j1]Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Yi Yao, Mayank Goswami, Chao Chen, Dimitris N. Metaxas:
Manifold-driven decomposition for adversarial robustness. Frontiers Comput. Sci. 5 (2023) - [c12]Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka:
Risk Bounds on Aleatoric Uncertainty Recovery. AISTATS 2023: 6015-6036 - [c11]Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen:
Learning to Segment from Noisy Annotations: A Spatial Correction Approach. ICLR 2023 - [c10]Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka:
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. ICML 2023: 4485-4513 - [c9]Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. NeurIPS 2023 - [i13]Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka:
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. CoRR abs/2305.07247 (2023) - [i12]Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. CoRR abs/2306.05671 (2023) - [i11]Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen:
Learning to Segment from Noisy Annotations: A Spatial Correction Approach. CoRR abs/2308.02498 (2023) - [i10]Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen:
Learning to Abstain From Uninformative Data. CoRR abs/2309.14240 (2023) - 2022
- [c8]Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Mayank Goswami, Chao Chen, Dimitris N. Metaxas:
A Manifold View of Adversarial Risk. AISTATS 2022: 11598-11614 - [c7]Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami:
Stability of SGD: Tightness analysis and improved bounds. UAI 2022: 2364-2373 - [i9]Wenjia Zhang, Yikai Zhang, Xiaolin Hu, Mayank Goswami, Chao Chen, Dimitris N. Metaxas:
A Manifold View of Adversarial Risk. CoRR abs/2203.13277 (2022) - [i8]Yikai Zhang, Jiachen Yao, Yusu Wang, Chao Chen:
On the Convergence of Optimizing Persistent-Homology-Based Losses. CoRR abs/2206.02946 (2022) - 2021
- [c6]Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen:
Learning with Feature-Dependent Label Noise: A Progressive Approach. ICLR 2021 - [c5]Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen:
Topological Detection of Trojaned Neural Networks. NeurIPS 2021: 17258-17272 - [i7]Yikai Zhang, Hui Qu, Qi Chang, Huidong Liu, Dimitris N. Metaxas, Chao Chen:
Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach. CoRR abs/2102.04655 (2021) - [i6]Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami:
Stability of SGD: Tightness Analysis and Improved Bounds. CoRR abs/2102.05274 (2021) - [i5]Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen:
Learning with Feature-Dependent Label Noise: A Progressive Approach. CoRR abs/2103.07756 (2021) - [i4]Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen:
Topological Detection of Trojaned Neural Networks. CoRR abs/2106.06469 (2021) - 2020
- [c4]Yikai Zhang, Hui Qu, Dimitris N. Metaxas, Chao Chen:
Local Regularizer Improves Generalization. AAAI 2020: 6861-6868 - [c3]Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas:
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data. CVPR 2020: 13853-13863 - [c2]Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris N. Metaxas:
Learn Distributed GAN with Temporary Discriminators. ECCV (27) 2020: 175-192 - [i3]Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas:
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data. CoRR abs/2006.00080 (2020) - [i2]Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris N. Metaxas:
Learn distributed GAN with Temporary Discriminators. CoRR abs/2007.09221 (2020) - [i1]Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu, Yikai Zhang, Tong Zhang, Shaoting Zhang, Dimitris N. Metaxas:
Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information. CoRR abs/2012.08604 (2020)
2010 – 2019
- 2019
- [c1]Yikai Zhang, Hui Qu, Chao Chen, Dimitris N. Metaxas:
Taming the Noisy Gradient: Train Deep Neural Networks with Small Batch Sizes. IJCAI 2019: 4348-4354
Coauthor Index
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last updated on 2024-11-19 21:48 CET by the dblp team
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