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T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP.

J. Teng, Z. Tan, и Y. Yuan. ICML, том 139 из Proceedings of Machine Learning Research, стр. 10203-10213. PMLR, (2021)

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Jiaye Huang

Beina Teng

Lichao Teng

Teng Fu

Kang Teng

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Finding Generalization Measures by Contrasting Signal and Noise.J. Teng, B. Zhang, R. Li, H. He, Y. Wang, Y. Tian, и Y. Yuan. ICML, том 202 из Proceedings of Machine Learning Research, стр. 33983-34010. PMLR, (2023)Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis.J. Teng, W. Huang, и H. He. AISTATS, том 151 из Proceedings of Machine Learning Research, стр. 4198-4216. PMLR, (2022)On Uni-Modal Feature Learning in Supervised Multi-Modal Learning.C. Du, J. Teng, T. Li, Y. Liu, T. Yuan, Y. Wang, Y. Yuan, и H. Zhao. ICML, том 202 из Proceedings of Machine Learning Research, стр. 8632-8656. PMLR, (2023)Towards Understanding Generalization via Decomposing Excess Risk Dynamics.J. Teng, J. Ma, и Y. Yuan. ICLR, OpenReview.net, (2022)T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP.J. Teng, Z. Tan, и Y. Yuan. ICML, том 139 из Proceedings of Machine Learning Research, стр. 10203-10213. PMLR, (2021)Predictive Inference with Feature Conformal Prediction.J. Teng, C. Wen, D. Zhang, Y. Bengio, Y. Gao, и Y. Yuan. ICLR, OpenReview.net, (2023)Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models.K. Wen, J. Teng, и J. Zhang. ICLR, OpenReview.net, (2023)Towards Understanding Generalization via Decomposing Excess Risk Dynamics.J. Teng, J. Ma, и Y. Yuan. CoRR, (2021)Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming.C. Wen, J. Qian, J. Lin, J. Teng, D. Jayaraman, и Y. Gao. ICML, том 162 из Proceedings of Machine Learning Research, стр. 23723-23750. PMLR, (2022)

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