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Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling
Current autoencoder-based disentangled representation learning methods a...
10/25/2020 ∙ by Akash Srivastava, et al. ∙
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For self-supervised learning, Rationality implies generalization, provably
We prove a new upper bound on the generalization gap of classifiers that...
10/16/2020 ∙ by Yamini Bansal, et al. ∙
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Distributional Generalization: A New Kind of Generalization
We introduce a new notion of generalization – Distributional Generalizat...
09/17/2020 ∙ by Preetum Nakkiran, et al. ∙
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Deep Double Descent: Where Bigger Models and More Data Hurt
We show that a variety of modern deep learning tasks exhibit a "double-d...
12/04/2019 ∙ by Preetum Nakkiran, et al. ∙
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Minnorm training: an algorithm for training over-parameterized deep neural networks
In this work, we propose a new training method for finding minimum weigh...
06/03/2018 ∙ by Yamini Bansal, et al. ∙
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Minnorm training: an algorithm for training overcomplete deep neural networks
In this work, we propose a new training method for finding minimum weigh...
06/03/2018 ∙ by Yamini Bansal, et al. ∙
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