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Disambiguation of "Wei, Colin"

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Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation.

, and . NeurIPS, page 9722-9733. (2019)

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Maité Colin

Samuel Colin

Hansjoachim Colin

Carmen Colinas Schwarz

Wei Wei

 

Other publications of authors with the same name

Theoretical insights on generalization in supervised and self-supervised deep learning.. Stanford University, USA, (2022)Shape Matters: Understanding the Implicit Bias of the Noise Covariance., , , and . CoRR, (2020)Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence., , , and . CoRR, (2022)Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel., , , and . NeurIPS, page 9709-9721. (2019)Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss., , , , and . NeurIPS, page 1565-1576. (2019)Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data., , , and . ICLR, OpenReview.net, (2021)Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss., , , and . NeurIPS, page 5000-5011. (2021)The Implicit and Explicit Regularization Effects of Dropout., , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 10181-10192. PMLR, (2020)Markov Chain Truncation for Doubly-Intractable Inference., and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 776-784. PMLR, (2017)Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel, , , and . (2018)cite arxiv:1810.05369Comment: version 2: title changed from originally Ön the Margin Theory of Feedforward Neural Networks". Substantial changes from old version of paper, including a new lower bound on NTK sample complexity version 3: reorganized NTK lower bound proof.