91 citations · 197 across the 14 of their papers we have counts for
15 papers
Parameter-free Stochastic Optimization of Variationally Coherent Functions
Francesco Orabona, Dávid Pál
We design and analyze an algorithm for first-order stochastic optimization of a large class of functions on . In particular, we consider the \emph{variationally coher…
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…
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
Alina Beygelzimer, Dávid Pál, Balázs Szörényi +3
We study the problem of efficient online multiclass linear classification with bandit feedback, where all examples belong to one of classes and lie in the -dimensional Eucli…
The information-theoretic value of unlabeled data in semi-supervised learning
Alexander Golovnev, Dávid Pál, Balázs Szörényi
We quantify the separation between the numbers of labeled examples required to learn in two settings: Settings with and without the knowledge of the distribution of the unlabeled d…
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
Satyen Kale, Zohar Karnin, Tengyuan Liang +1
Online sparse linear regression is an online problem where an algorithm repeatedly chooses a subset of coordinates to observe in an adversarially chosen feature vector, makes a rea…
Coin Betting and Parameter-Free Online Learning
Francesco Orabona, Dávid Pál
In the recent years, a number of parameter-free algorithms have been developed for online linear optimization over Hilbert spaces and for learning with expert advice. These algorit…