
On MarginBased Cluster Recovery with Oracle Queries
We study an active cluster recovery problem where, given a set of n poin...
read it

Beyond Bandit Feedback in Online Multiclass Classification
We study the problem of online multiclass classification in a setting wh...
read it

Multitask Online Mirror Descent
We introduce and analyze MTOMD, a multitask generalization of Online Mi...
read it

MultiSided Matching Markets with Consistent Preferences and Cooperative Partners
We introduce a variant of the threesided stable matching problem for a ...
read it

An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
We propose an algorithm for stochastic and adversarial multiarmed bandit...
read it

A Regret Analysis of Bilateral Trade
Bilateral trade, a fundamental topic in economics, models the problem of...
read it

Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries
We investigate the problem of exact cluster recovery using oracle querie...
read it

TwoSided Matching Markets in the ELLIS 2020 PhD Program
The ELLIS PhD program is a European initiative that supports excellent y...
read it

Exact Recovery of Mangled Clusters with SameCluster Queries
We study the problem of recovering distorted clusters in the semisuperv...
read it

LocallyAdaptive Nonparametric Online Learning
One of the main strengths of online algorithms is their ability to adapt...
read it

Stochastic Bandits with DelayDependent Payoffs
Motivated by recommendation problems in music streaming platforms, we pr...
read it

Nonstochastic Multiarmed Bandits with Unrestricted Delays
We investigate multiarmed bandits with delayed feedback, where the delay...
read it

Correlation Clustering with Adaptive Similarity Queries
We investigate learning algorithms that use similarity queries to approx...
read it

Repeated A/B Testing
We study a setting in which a learner faces a sequence of A/B tests and ...
read it

DistributionDependent Analysis of GibbsERM Principle
GibbsERM learning is a natural idealized model of learning with stochas...
read it

Cooperative Online Learning: Keeping your Neighbors Updated
We study an asynchronous online learning setting with a network of agent...
read it

Efficient Linear Bandits through Matrix Sketching
We prove that two popular linear contextual bandit algorithms, OFUL and ...
read it

Dynamic Pricing with Finitely Many Unknown Valuations
Motivated by posted price auctions where buyers are grouped in an unknow...
read it

Combining CostSensitive Classification with Negative Selection for Protein Function Prediction
Motivation: Computational methods play a central role in annotating the ...
read it

Boltzmann Exploration Done Right
Boltzmann exploration is a classic strategy for sequential decisionmaki...
read it

Bandit Regret Scaling with the Effective Loss Range
We study how the regret guarantees of nonstochastic multiarmed bandits ...
read it

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
We investigate contextual online learning with nonparametric (Lipschitz)...
read it

Multitask Protein Function Prediction Through Task Dissimilarity
Automated protein function prediction is a challenging problem with dist...
read it

Active Learning for Online Recognition of Human Activities from Streaming Videos
Recognising human activities from streaming videos poses unique challeng...
read it

The ABACOC Algorithm: a Novel Approach for Nonparametric Classification of Data Streams
Stream mining poses unique challenges to machine learning: predictive mo...
read it

On the Complexity of Learning with Kernels
A wellrecognized limitation of kernel learning is the requirement to ha...
read it

Nonstochastic MultiArmed Bandits with GraphStructured Feedback
We present and study a partialinformation model of online learning, whe...
read it

From Bandits to Experts: A Tale of Domination and Independence
We consider the partial observability model for multiarmed bandits, int...
read it

A Gang of Bandits
Multiarmed bandit problems are receiving a great deal of attention beca...
read it

Online Learning with Switching Costs and Other Adaptive Adversaries
We study the power of different types of adaptive (nonoblivious) adversa...
read it

Active Learning on Trees and Graphs
We investigate the problem of active learning on a given tree whose node...
read it

A Correlation Clustering Approach to Link Classification in Signed Networks  Full Version 
Motivated by social balance theory, we develop a theory of link classifi...
read it

A Linear Time Active Learning Algorithm for Link Classification  Full Version 
We present very efficient active learning algorithms for link classifica...
read it

Random Spanning Trees and the Prediction of Weighted Graphs
We investigate the problem of sequentially predicting the binary labels ...
read it

Bandits with heavy tail
The stochastic multiarmed bandit problem is well understood when the re...
read it

Regret Analysis of Stochastic and Nonstochastic Multiarmed Bandit Problems
Multiarmed bandit problems are the most basic examples of sequential de...
read it

Mirror Descent Meets Fixed Share (and feels no regret)
Mirror descent with an entropic regularizer is known to achieve shifting...
read it

Towards minimax policies for online linear optimization with bandit feedback
We address the online linear optimization problem with bandit feedback. ...
read it

PACBayesian Inequalities for Martingales
We present a set of highprobability inequalities that control the conce...
read it

An Optimal Algorithm for Linear Bandits
We provide the first algorithm for online bandit linear optimization who...
read it

Efficient Transductive Online Learning via Randomized Rounding
Most traditional online learning algorithms are based on variants of mir...
read it

PACBayesian Analysis of the ExplorationExploitation Tradeoff
We develop a coherent framework for integrative simultaneous analysis of...
read it