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ORCIDYaodong Yu
- > Home > Persons > Yaodong Yu
Publications
- 2025
[c28]Ziyang Wu, Tianjiao Ding, Yifu Lu, Druv Pai, Jingyuan Zhang, Weida Wang, Yaodong Yu, Yi Ma, Benjamin David Haeffele:
Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction. ICLR 2025- [i37]Peng Wang, Yifu Lu, Yaodong Yu, Druv Pai, Qing Qu, Yi Ma:
Attention-Only Transformers via Unrolled Subspace Denoising. CoRR abs/2506.03790 (2025) - 2024
- [c27]Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma:
Emergence of Segmentation with Minimalistic White-Box Transformers. CPAL 2024: 72-93 - [c26]Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma:
Masked Completion via Structured Diffusion with White-Box Transformers. ICLR 2024 - [c25]Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu
, Yi Ma:
A Global Geometric Analysis of Maximal Coding Rate Reduction. ICML 2024 - [c24]Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Oliviero Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
Differentially Private Representation Learning via Image Captioning. ICML 2024 - [c23]Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
ViP: A Differentially Private Foundation Model for Computer Vision. ICML 2024 - [c21]Jinrui Yang, Xianhang Li, Druv Pai, Yuyin Zhou, Yi Ma, Yaodong Yu, Cihang Xie:
Scaling White-Box Transformers for Vision. NeurIPS 2024 - [i36]Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
Differentially Private Representation Learning via Image Captioning. CoRR abs/2403.02506 (2024) - [i35]Druv Pai, Ziyang Wu, Sam Buchanan, Yaodong Yu, Yi Ma:
Masked Completion via Structured Diffusion with White-Box Transformers. CoRR abs/2404.02446 (2024) - [i34]Jinrui Yang, Xianhang Li, Druv Pai, Yuyin Zhou, Yi Ma, Yaodong Yu, Cihang Xie:
Scaling White-Box Transformers for Vision. CoRR abs/2405.20299 (2024) - [i33]Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu, Yi Ma:
A Global Geometric Analysis of Maximal Coding Rate Reduction. CoRR abs/2406.01909 (2024) - [i29]Ziyang Wu, Tianjiao Ding, Yifu Lu, Druv Pai, Jingyuan Zhang, Weida Wang, Yaodong Yu, Yi Ma, Benjamin D. Haeffele:
Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction. CoRR abs/2412.17810 (2024) - 2023
- [c19]Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma:
White-Box Transformers via Sparse Rate Reduction. NeurIPS 2023 - [i27]Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma:
White-Box Transformers via Sparse Rate Reduction. CoRR abs/2306.01129 (2023) - [i26]Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
ViP: A Differentially Private Foundation Model for Computer Vision. CoRR abs/2306.08842 (2023) - [i25]Yaodong Yu, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan:
Scaff-PD: Communication Efficient Fair and Robust Federated Learning. CoRR abs/2307.13381 (2023) - [i24]Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma:
Emergence of Segmentation with Minimalistic White-Box Transformers. CoRR abs/2308.16271 (2023) - [i23]Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma:
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? CoRR abs/2311.13110 (2023) - 2022
- [j2]Xili Dai, Shengbang Tong, Mingyang Li, Ziyang Wu, Michael Psenka, Kwan Ho Ryan Chan, Pengyuan Zhai, Yaodong Yu, Xiaojun Yuan, Heung-Yeung Shum, Yi Ma:
CTRL: Closed-Loop Transcription to an LDR via Minimaxing Rate Reduction. Entropy 24(4): 456 (2022) - [j1]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. J. Mach. Learn. Res. 23: 114:1-114:103 (2022) - [c17]Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan:
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging. AISTATS 2022: 9793-9826 - [c14]Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, Jacob Steinhardt:
Predicting Out-of-Distribution Error with the Projection Norm. ICML 2022: 25721-25746 - [c12]Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan:
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels. NeurIPS 2022 - [c11]Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Jordan:
Robust Calibration with Multi-domain Temperature Scaling. NeurIPS 2022 - [i21]Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, Jacob Steinhardt:
Predicting Out-of-Distribution Error with the Projection Norm. CoRR abs/2202.05834 (2022) - [i17]Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Jordan:
Robust Calibration with Multi-domain Temperature Scaling. CoRR abs/2206.02757 (2022) - [i16]Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan:
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels. CoRR abs/2207.06343 (2022) - 2021
- [c10]Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, Yuan Yao:
Adversarial Robustness of Stabilized Neural ODE Might be from Obfuscated Gradients. MSML 2021: 497-515 - [i15]Yaodong Yu, Zitong Yang, Edgar Dobriban, Jacob Steinhardt, Yi Ma:
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition. CoRR abs/2103.09947 (2021) - [i13]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. CoRR abs/2105.10446 (2021) - [i12]Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan:
On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging. CoRR abs/2107.00464 (2021) - [i11]Xili Dai, Shengbang Tong, Mingyang Li, Ziyang Wu, Kwan Ho Ryan Chan, Pengyuan Zhai, Yaodong Yu, Michael Psenka, Xiaojun Yuan, Heung-Yeung Shum, Yi Ma:
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction. CoRR abs/2111.06636 (2021) - 2020
- [c9]Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma:
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. ICML 2020: 10767-10777 - [c7]Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma:
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. NeurIPS 2020 - [i9]Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma:
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. CoRR abs/2002.11328 (2020) - [i8]Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma:
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. CoRR abs/2006.08558 (2020) - [i6]Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, Yuan Yao:
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients. CoRR abs/2009.13145 (2020) - [i5]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
Deep Networks from the Principle of Rate Reduction. CoRR abs/2010.14765 (2020)
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last updated on 2025-08-22 02:13 CEST by the dblp team
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