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Rethinking Bias-Variance Trade-off for Generalization of Neural Networks

Z. Yang, Y. Yu, C. You, J. Steinhardt, и Y. Ma. Proceedings of the 37th International Conference on Machine Learning, том 119 из Proceedings of Machine Learning Research, стр. 10767--10777. PMLR, (13--18 Jul 2020)

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Yaodong Yang

Yaodong Wu

Yaodong Zhang

Yu-Ting Yu

Yu-Yu Su

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White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?Y. Yu, S. Buchanan, D. Pai, T. Chu, Z. Wu, S. Tong, H. Bai, Y. Zhai, B. Haeffele, и Y. Ma. CoRR, (2023)TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels.Y. Yu, A. Wei, S. Karimireddy, Y. Ma, и M. Jordan. NeurIPS, (2022)Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization.Y. Yu, T. Lin, E. Mazumdar, и M. Jordan. AISTATS, том 151 из Proceedings of Machine Learning Research, стр. 1219-1250. PMLR, (2022)Learning One-hidden-layer ReLU Networks via Gradient Descent.X. Zhang, Y. Yu, L. Wang, и Q. Gu. AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 1524-1534. PMLR, (2019)Scaling White-Box Transformers for Vision.J. Yang, X. Li, D. Pai, Y. Zhou, Y. Ma, Y. Yu, и C. Xie. CoRR, (2024)What You See is What You Get: Principled Deep Learning via Distributional Generalization.B. Kulynych, Y. Yang, Y. Yu, J. Blasiok, и P. Nakkiran. NeurIPS, (2022)Robust Calibration with Multi-domain Temperature Scaling.Y. Yu, S. Bates, Y. Ma, и M. Jordan. NeurIPS, (2022)Federated Conformal Predictors for Distributed Uncertainty Quantification.C. Lu, Y. Yu, S. Karimireddy, M. Jordan, и R. Raskar. ICML, том 202 из Proceedings of Machine Learning Research, стр. 22942-22964. PMLR, (2023)Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation.A. Sanyal, Y. Hu, Y. Yu, Y. Ma, Y. Wang, и B. Schölkopf. CoRR, (2024)CTRL: Closed-Loop Transcription to an LDR via Minimaxing Rate Reduction.X. Dai, S. Tong, M. Li, Z. Wu, M. Psenka, K. Chan, P. Zhai, Y. Yu, X. Yuan, H. Shum и 1 other автор(ы). Entropy, 24 (4): 456 (2022)

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