
Stochastic Bandits with DelayDependent Payoffs
Motivated by recommendation problems in music streaming platforms, we pr...
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Cooperative Online Learning: Keeping your Neighbors Updated
We study an asynchronous online learning setting with a network of agent...
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LocallyAdaptive Nonparametric Online Learning
One of the main strengths of online algorithms is their ability to adapt...
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Boltzmann Exploration Done Right
Boltzmann exploration is a classic strategy for sequential decisionmaki...
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Bandit Regret Scaling with the Effective Loss Range
We study how the regret guarantees of nonstochastic multiarmed bandits ...
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Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
We investigate contextual online learning with nonparametric (Lipschitz)...
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Multitask Protein Function Prediction Through Task Dissimilarity
Automated protein function prediction is a challenging problem with dist...
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The ABACOC Algorithm: a Novel Approach for Nonparametric Classification of Data Streams
Stream mining poses unique challenges to machine learning: predictive mo...
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Active Learning for Online Recognition of Human Activities from Streaming Videos
Recognising human activities from streaming videos poses unique challeng...
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On the Complexity of Learning with Kernels
A wellrecognized limitation of kernel learning is the requirement to ha...
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Nonstochastic MultiArmed Bandits with GraphStructured Feedback
We present and study a partialinformation model of online learning, whe...
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From Bandits to Experts: A Tale of Domination and Independence
We consider the partial observability model for multiarmed bandits, int...
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A Gang of Bandits
Multiarmed bandit problems are receiving a great deal of attention beca...
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Online Learning with Switching Costs and Other Adaptive Adversaries
We study the power of different types of adaptive (nonoblivious) adversa...
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Active Learning on Trees and Graphs
We investigate the problem of active learning on a given tree whose node...
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A Correlation Clustering Approach to Link Classification in Signed Networks  Full Version 
Motivated by social balance theory, we develop a theory of link classifi...
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A Linear Time Active Learning Algorithm for Link Classification  Full Version 
We present very efficient active learning algorithms for link classifica...
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Random Spanning Trees and the Prediction of Weighted Graphs
We investigate the problem of sequentially predicting the binary labels ...
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Bandits with heavy tail
The stochastic multiarmed bandit problem is well understood when the re...
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Regret Analysis of Stochastic and Nonstochastic Multiarmed Bandit Problems
Multiarmed bandit problems are the most basic examples of sequential de...
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Mirror Descent Meets Fixed Share (and feels no regret)
Mirror descent with an entropic regularizer is known to achieve shifting...
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Towards minimax policies for online linear optimization with bandit feedback
We address the online linear optimization problem with bandit feedback. ...
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PACBayesian Inequalities for Martingales
We present a set of highprobability inequalities that control the conce...
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An Optimal Algorithm for Linear Bandits
We provide the first algorithm for online bandit linear optimization who...
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Efficient Transductive Online Learning via Randomized Rounding
Most traditional online learning algorithms are based on variants of mir...
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PACBayesian Analysis of the ExplorationExploitation Tradeoff
We develop a coherent framework for integrative simultaneous analysis of...
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Combining CostSensitive Classification with Negative Selection for Protein Function Prediction
Motivation: Computational methods play a central role in annotating the ...
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Dynamic Pricing with Finitely Many Unknown Valuations
Motivated by posted price auctions where buyers are grouped in an unknow...
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Efficient Linear Bandits through Matrix Sketching
We prove that two popular linear contextual bandit algorithms, OFUL and ...
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DistributionDependent Analysis of GibbsERM Principle
GibbsERM learning is a natural idealized model of learning with stochas...
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Repeated A/B Testing
We study a setting in which a learner faces a sequence of A/B tests and ...
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Correlation Clustering with Adaptive Similarity Queries
We investigate learning algorithms that use similarity queries to approx...
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Nonstochastic Multiarmed Bandits with Unrestricted Delays
We investigate multiarmed bandits with delayed feedback, where the delay...
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