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08/15/2023
High-Probability Risk Bounds via Sequential Predictors
Online learning methods yield sequential regret bounds under minimal ass...
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08/03/2023
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning
Multitask learning is a powerful framework that enables one to simultane...
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07/14/2023
The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations
We study the problem of regret minimization for a single bidder in a seq...
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07/03/2023
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
We investigate online classification with paid stochastic experts. Here,...
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05/30/2023
Delayed Bandits: When Do Intermediate Observations Help?
We study a K-armed bandit with delayed feedback and intermediate observa...
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05/24/2023
On the Minimax Regret for Online Learning with Feedback Graphs
In this work, we improve on the upper and lower bounds for the regret of...
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05/15/2023
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs
We derive a new analysis of Follow The Regularized Leader (FTRL) for onl...
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03/14/2023
Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice
We investigate the problem of bandits with expert advice when the expert...
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02/21/2023
Repeated Bilateral Trade Against a Smoothed Adversary
We study repeated bilateral trade where an adaptive σ-smooth adversary g...
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02/16/2023
Linear Bandits with Memory: from Rotting to Rising
Nonstationary phenomena, such as satiation effects in recommendation, ar...
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10/09/2022
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
The framework of feedback graphs is a generalization of sequential decis...
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09/08/2022
Active Learning of Classifiers with Label and Seed Queries
We study exact active learning of binary and multiclass classifiers with...
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07/08/2022
Online Learning in Supply-Chain Games
We study a repeated game between a supplier and a retailer who want to m...
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06/06/2022
A Regret-Variance Trade-Off in Online Learning
We consider prediction with expert advice for strongly convex and bounde...
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06/01/2022
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs
We consider online learning with feedback graphs, a sequential decision-...
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05/31/2022
AdaTask: Adaptive Multitask Online Learning
We introduce and analyze AdaTask, a multitask online learning algorithm ...
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12/06/2021
Nonstochastic Bandits with Composite Anonymous Feedback
We investigate a nonstochastic bandit setting in which the loss of an ac...
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11/02/2021
Nonstochastic Bandits and Experts with Arm-Dependent Delays
We study nonstochastic bandits and experts in a delayed setting where de...
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10/22/2021
Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality
Motivated by the fact that humans like some level of unpredictability or...
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09/08/2021
Bilateral Trade: A Regret Minimization Perspective
Bilateral trade, a fundamental topic in economics, models the problem of...
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06/09/2021
On Margin-Based Cluster Recovery with Oracle Queries
We study an active cluster recovery problem where, given a set of n poin...
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06/07/2021
Beyond Bandit Feedback in Online Multiclass Classification
We study the problem of online multiclass classification in a setting wh...
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06/04/2021
Multitask Online Mirror Descent
We introduce and analyze MT-OMD, a multitask generalization of Online Mi...
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02/23/2021
Multi-Sided Matching Markets with Consistent Preferences and Cooperative Partners
We introduce a variant of the three-sided stable matching problem for a ...
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02/19/2021
An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
We propose an algorithm for stochastic and adversarial multiarmed bandit...
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02/16/2021
A Regret Analysis of Bilateral Trade
Bilateral trade, a fundamental topic in economics, models the problem of...
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01/31/2021
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries
We investigate the problem of exact cluster recovery using oracle querie...
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01/28/2021
Two-Sided Matching Markets in the ELLIS 2020 PhD Program
The ELLIS PhD program is a European initiative that supports excellent y...
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06/08/2020
Exact Recovery of Mangled Clusters with Same-Cluster Queries
We study the problem of recovering distorted clusters in the semi-superv...
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02/05/2020
Locally-Adaptive Nonparametric Online Learning
One of the main strengths of online algorithms is their ability to adapt...
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10/07/2019
Stochastic Bandits with Delay-Dependent Payoffs
Motivated by recommendation problems in music streaming platforms, we pr...
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06/03/2019
Nonstochastic Multiarmed Bandits with Unrestricted Delays
We investigate multiarmed bandits with delayed feedback, where the delay...
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05/28/2019
Correlation Clustering with Adaptive Similarity Queries
We investigate learning algorithms that use similarity queries to approx...
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05/28/2019
Repeated A/B Testing
We study a setting in which a learner faces a sequence of A/B tests and ...
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02/05/2019
Distribution-Dependent Analysis of Gibbs-ERM Principle
Gibbs-ERM learning is a natural idealized model of learning with stochas...
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01/23/2019
Cooperative Online Learning: Keeping your Neighbors Updated
We study an asynchronous online learning setting with a network of agent...
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09/28/2018
Efficient Linear Bandits through Matrix Sketching
We prove that two popular linear contextual bandit algorithms, OFUL and ...
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07/09/2018
Dynamic Pricing with Finitely Many Unknown Valuations
Motivated by posted price auctions where buyers are grouped in an unknow...
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05/18/2018
Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction
Motivation: Computational methods play a central role in annotating the ...
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05/29/2017
Boltzmann Exploration Done Right
Boltzmann exploration is a classic strategy for sequential decision-maki...
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05/15/2017
Bandit Regret Scaling with the Effective Loss Range
We study how the regret guarantees of nonstochastic multi-armed bandits ...
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02/27/2017
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
We investigate contextual online learning with nonparametric (Lipschitz)...
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11/03/2016
Multitask Protein Function Prediction Through Task Dissimilarity
Automated protein function prediction is a challenging problem with dist...
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04/11/2016
Active Learning for Online Recognition of Human Activities from Streaming Videos
Recognising human activities from streaming videos poses unique challeng...
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08/20/2015
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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11/05/2014
On the Complexity of Learning with Kernels
A well-recognized limitation of kernel learning is the requirement to ha...
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09/30/2014
Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback
We present and study a partial-information model of online learning, whe...
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07/17/2013
From Bandits to Experts: A Tale of Domination and Independence
We consider the partial observability model for multi-armed bandits, int...
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06/04/2013
A Gang of Bandits
Multi-armed bandit problems are receiving a great deal of attention beca...
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02/18/2013