20 citations · 43 across the 5 of their papers we have counts for
8 papers
Learning from Randomly Initialized Neural Network Features
Ehsan Amid, Rohan Anil, Wojciech Kotłowski +1
We present the surprising result that randomly initialized neural networks are good feature extractors in expectation. These random features correspond to finite-sample realization…
Robust Online Convex Optimization in the Presence of Outliers
Tim van Erven, Sarah Sachs, Wouter M. Koolen +1
We consider online convex optimization when a number k of data points are outliers that may be corrupted. We model this by introducing the notion of robust regret, which measures t…
A case where a spindly two-layer linear network whips any neural network with a fully connected input layer
Manfred K. Warmuth, Wojciech Kotłowski, Ehsan Amid
It was conjectured that any neural network of any structure and arbitrary differentiable transfer functions at the nodes cannot learn the following problem sample efficiently when…
Learning to Crawl
Utkarsh Upadhyay, Robert Busa-Fekete, Wojciech Kotlowski +2
Web crawling is the problem of keeping a cache of webpages fresh, i.e., having the most recent copy available when a page is requested. This problem is usually coupled with the nat…
Adaptive scale-invariant online algorithms for learning linear models
Michał Kempka, Wojciech Kotłowski, Manfred K. Warmuth
We consider online learning with linear models, where the algorithm predicts on sequentially revealed instances (feature vectors), and is compared against the best linear function…
Bandit Principal Component Analysis
Wojciech Kotłowski, Gergely Neu
We consider a partial-feedback variant of the well-studied online PCA problem where a learner attempts to predict a sequence of -dimensional vectors in terms of a quadratic loss…