Nicolò Cesa-Bianchi

research

∙ 08/15/2023

High-Probability Risk Bounds via Sequential Predictors

Online learning methods yield sequential regret bounds under minimal ass...

0 Dirk van der Hoeven, et al. ∙

research

∙ 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...

0 Pier Giuseppe Sessa, et al. ∙

research

∙ 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...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 07/03/2023

Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts

We investigate online classification with paid stochastic experts. Here,...

0 Dirk van der Hoeven, et al. ∙

research

∙ 05/30/2023

Delayed Bandits: When Do Intermediate Observations Help?

We study a K-armed bandit with delayed feedback and intermediate observa...

0 Emmanuel Esposito, et al. ∙

research

∙ 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...

0 Khaled Eldowa, et al. ∙

research

∙ 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...

0 Dirk van der Hoeven, et al. ∙

research

∙ 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...

0 Khaled Eldowa, et al. ∙

research

∙ 02/21/2023

Repeated Bilateral Trade Against a Smoothed Adversary

We study repeated bilateral trade where an adaptive σ-smooth adversary g...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 02/16/2023

Linear Bandits with Memory: from Rotting to Rising

Nonstationary phenomena, such as satiation effects in recommendation, ar...

0 Giulia Clerici, et al. ∙

research

∙ 10/09/2022

Learning on the Edge: Online Learning with Stochastic Feedback Graphs

The framework of feedback graphs is a generalization of sequential decis...

0 Emmanuel Esposito, et al. ∙

research

∙ 09/08/2022

Active Learning of Classifiers with Label and Seed Queries

We study exact active learning of binary and multiclass classifiers with...

4 Marco Bressan, et al. ∙

research

∙ 07/08/2022

Online Learning in Supply-Chain Games

We study a repeated game between a supplier and a retailer who want to m...

10 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 06/06/2022

A Regret-Variance Trade-Off in Online Learning

We consider prediction with expert advice for strongly convex and bounde...

6 Dirk van der Hoeven, et al. ∙

research

∙ 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-...

0 Chloé Rouyer, et al. ∙

research

∙ 05/31/2022

AdaTask: Adaptive Multitask Online Learning

We introduce and analyze AdaTask, a multitask online learning algorithm ...

0 Pierre Laforgue, et al. ∙

research

∙ 12/06/2021

Nonstochastic Bandits with Composite Anonymous Feedback

We investigate a nonstochastic bandit setting in which the loss of an ac...

4 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 11/02/2021

Nonstochastic Bandits and Experts with Arm-Dependent Delays

We study nonstochastic bandits and experts in a delayed setting where de...

0 Dirk van der Hoeven, et al. ∙

research

∙ 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...

5 Pierre Laforgue, et al. ∙

research

∙ 09/08/2021

Bilateral Trade: A Regret Minimization Perspective

Bilateral trade, a fundamental topic in economics, models the problem of...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 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...

0 Marco Bressan, et al. ∙

research

∙ 06/07/2021

Beyond Bandit Feedback in Online Multiclass Classification

We study the problem of online multiclass classification in a setting wh...

0 Dirk van der Hoeven, et al. ∙

research

∙ 06/04/2021

Multitask Online Mirror Descent

We introduce and analyze MT-OMD, a multitask generalization of Online Mi...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 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 ...

0 Maximilian Mordig, et al. ∙

research

∙ 02/19/2021

An Algorithm for Stochastic and Adversarial Bandits with Switching Costs

We propose an algorithm for stochastic and adversarial multiarmed bandit...

14 Chloé Rouyer, et al. ∙

research

∙ 02/16/2021

A Regret Analysis of Bilateral Trade

Bilateral trade, a fundamental topic in economics, models the problem of...

9 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 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...

5 Marco Bressan, et al. ∙

research

∙ 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...

0 Maximilian Mordig, et al. ∙

research

∙ 06/08/2020

Exact Recovery of Mangled Clusters with Same-Cluster Queries

We study the problem of recovering distorted clusters in the semi-superv...

0 Marco Bressan, et al. ∙

research

∙ 02/05/2020

Locally-Adaptive Nonparametric Online Learning

One of the main strengths of online algorithms is their ability to adapt...

5 Ilja Kuzborskij, et al. ∙

research

∙ 10/07/2019

Stochastic Bandits with Delay-Dependent Payoffs

Motivated by recommendation problems in music streaming platforms, we pr...

28 Leonardo Cella, et al. ∙

research

∙ 06/03/2019

Nonstochastic Multiarmed Bandits with Unrestricted Delays

We investigate multiarmed bandits with delayed feedback, where the delay...

0 Tobias Sommer Thune, et al. ∙

research

∙ 05/28/2019

Correlation Clustering with Adaptive Similarity Queries

We investigate learning algorithms that use similarity queries to approx...

0 Marco Bressan, et al. ∙

research

∙ 05/28/2019

Repeated A/B Testing

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

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 02/05/2019

Distribution-Dependent Analysis of Gibbs-ERM Principle

Gibbs-ERM learning is a natural idealized model of learning with stochas...

0 Ilja Kuzborskij, et al. ∙

research

∙ 01/23/2019

Cooperative Online Learning: Keeping your Neighbors Updated

We study an asynchronous online learning setting with a network of agent...

18 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 09/28/2018

Efficient Linear Bandits through Matrix Sketching

We prove that two popular linear contextual bandit algorithms, OFUL and ...

0 Ilja Kuzborskij, et al. ∙

research

∙ 07/09/2018

Dynamic Pricing with Finitely Many Unknown Valuations

Motivated by posted price auctions where buyers are grouped in an unknow...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 05/18/2018

Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction

Motivation: Computational methods play a central role in annotating the ...

0 Marco Frasca, et al. ∙

research

∙ 05/29/2017

Boltzmann Exploration Done Right

Boltzmann exploration is a classic strategy for sequential decision-maki...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 05/15/2017

Bandit Regret Scaling with the Effective Loss Range

We study how the regret guarantees of nonstochastic multi-armed bandits ...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 02/27/2017

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning

We investigate contextual online learning with nonparametric (Lipschitz)...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 11/03/2016

Multitask Protein Function Prediction Through Task Dissimilarity

Automated protein function prediction is a challenging problem with dist...

0 Marco Frasca, et al. ∙

research

∙ 04/11/2016

Active Learning for Online Recognition of Human Activities from Streaming Videos

Recognising human activities from streaming videos poses unique challeng...

0 Rocco De Rosa, et al. ∙

research

∙ 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...

0 Rocco De Rosa, et al. ∙

research

∙ 11/05/2014

On the Complexity of Learning with Kernels

A well-recognized limitation of kernel learning is the requirement to ha...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 09/30/2014

Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback

We present and study a partial-information model of online learning, whe...

0 Noga Alon, et al. ∙

research

∙ 07/17/2013

From Bandits to Experts: A Tale of Domination and Independence

We consider the partial observability model for multi-armed bandits, int...

0 Noga Alon, et al. ∙

research

∙ 06/04/2013

A Gang of Bandits

Multi-armed bandit problems are receiving a great deal of attention beca...

0 Nicolò Cesa-Bianchi, et al. ∙

research

∙ 02/18/2013

Online Learning with Switching Costs and Other Adaptive Adversaries

We study the power of different types of adaptive (nonoblivious) adversa...

0 Nicolò Cesa-Bianchi, et al. ∙

Nicolò Cesa-Bianchi

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