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A case where a spindly two-layer linear network whips any neural network with a fully connected input layer
It was conjectured that any neural network of any structure and arbitrar...
10/16/2020 ∙ by Manfred K. Warmuth, et al. ∙
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Learning to Crawl
Web crawling is the problem of keeping a cache of webpages fresh, i.e., ...
05/29/2019 ∙ by Utkarsh Upadhyay, et al. ∙
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Adaptive scale-invariant online algorithms for learning linear models
We consider online learning with linear models, where the algorithm pred...
02/20/2019 ∙ by Michał Kempka, et al. ∙
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Bandit Principal Component Analysis
We consider a partial-feedback variant of the well-studied online PCA pr...
02/08/2019 ∙ by Wojciech Kotłowski, et al. ∙
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The Many Faces of Exponential Weights in Online Learning
A standard introduction to online learning might place Online Gradient D...
02/21/2018 ∙ by Dirk van der Hoeven, et al. ∙
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Scale-invariant unconstrained online learning
We consider a variant of online convex optimization in which both the in...
08/23/2017 ∙ by Wojciech Kotłowski, et al. ∙
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Online Isotonic Regression
We consider the online version of the isotonic regression problem. Given...
03/14/2016 ∙ by Wojciech Kotłowski, et al. ∙
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PCA with Gaussian perturbations
Most of machine learning deals with vector parameters. Ideally we would ...
06/16/2015 ∙ by Wojciech Kotłowski, et al. ∙
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Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
We study online learning under logarithmic loss with regular parametric ...
05/19/2013 ∙ by Peter Bartlett, et al. ∙
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Consistent Multilabel Ranking through Univariate Losses
We consider the problem of rank loss minimization in the setting of mult...
06/27/2012 ∙ by Krzysztof Dembczynski, et al. ∙
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