Cesa-Bianchi, Nicolò

129 publications

COLT 2025 A Fine-Grained Characterization of PAC Learnability Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

JMLR 2025 A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs Lukas Zierahn, Dirk van der Hoeven, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi

NeurIPS 2025 Dynamic Regret Reduces to Kernelized Static Regret Andrew Jacobsen, Alessandro Rudi, Francesco Orabona, Nicolò Cesa-Bianchi

JAIR 2025 Improved Regret Bounds for Bandits with Expert Advice Nicolò Cesa-Bianchi, Khaled Eldowa, Emmanuel Esposito, Julia Olkhovskaya

NeurIPS 2025 Instance-Dependent Regret Bounds for Nonstochastic Linear Partial Monitoring Federico Di Gennaro, Khaled Eldowa, Nicolò Cesa-Bianchi

COLT 2025 Market Making Without Regret Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Luigi Foscari, Vinayak Pathak

COLT 2025 Of Dice and Games: A Theory of Generalized Boosting Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

COLT 2024 A Theory of Interpretable Approximations Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

NeurIPSW 2024 A Theory of Interpretable Approximations Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

AISTATS 2024 Best-of-Both-Worlds Algorithms for Linear Contextual Bandits Yuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicolò Cesa-Bianchi

TMLR 2024 Cooperative Online Learning with Feedback Graphs Nicolò Cesa-Bianchi, Tommaso Cesari, Riccardo Della Vecchia

NeurIPS 2024 Fair Online Bilateral Trade François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni

JMLR 2024 Information Capacity Regret Bounds for Bandits with Mediator Feedback Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli

TMLR 2024 Linear Bandits with Memory Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi

JMLR 2024 Margin-Based Active Learning of Classifiers Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice

AISTATS 2024 Multitask Online Learning: Listen to the Neighborhood Buzz Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue

JMLR 2024 Regret Analysis of Bilateral Trade with a Smoothed Adversary Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi

NeurIPS 2024 Sparsity-Agnostic Linear Bandits with Adaptive Adversaries Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi

AISTATS 2024 Sum-Max Submodular Bandits Stephen U. Pasteris, Alberto Rumi, Fabio Vitale, Nicolò Cesa-Bianchi

ICMLW 2024 Sum-Max Submodular Bandits Stephen Pasteris, Alberto Rumi, Fabio Vitale, Nicolò Cesa-Bianchi

COLT 2023 A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs Dirk Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi

ICML 2023 Delayed Bandits: When Do Intermediate Observations Help? Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk Van Der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin

NeurIPS 2023 Multitask Learning with No Regret: From Improved Confidence Bounds to Active Learning Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause

AISTATS 2023 Nonstochastic Contextual Combinatorial Bandits Lukas Zierahn, Dirk Hoeven, Nicolò Cesa-Bianchi, Gergely Neu

NeurIPS 2023 On the Minimax Regret for Online Learning with Feedback Graphs Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi

COLT 2023 Repeated Bilateral Trade Against a Smoothed Adversary Nicolò Cesa-Bianchi, Tommaso R. Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi

ICML 2023 Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts Dirk Van Der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi

AISTATS 2022 A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach

AISTATS 2022 Nonstochastic Bandits and Experts with Arm-Dependent Delays Dirk Van Der Hoeven, Nicolò Cesa-Bianchi

NeurIPS 2022 A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin

NeurIPS 2022 A Regret-Variance Trade-Off in Online Learning Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi

NeurIPS 2022 Active Learning of Classifiers with Label and Seed Queries Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen

NeurIPS 2022 Learning on the Edge: Online Learning with Stochastic Feedback Graphs Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi

TMLR 2022 Multitask Online Mirror Descent Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil

JMLR 2022 Nonstochastic Bandits with Composite Anonymous Feedback Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour

ICML 2021 An Algorithm for Stochastic and Adversarial Bandits with Switching Costs Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi

NeurIPS 2021 Beyond Bandit Feedback in Online Multiclass Classification Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi

COLT 2021 Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries Marco Bressan, Nicoló Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice

NeurIPS 2021 On Margin-Based Cluster Recovery with Oracle Queries Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice

NeurIPS 2021 ROI Maximization in Stochastic Online Decision-Making Nicolò Cesa-Bianchi, Tom Cesari, Yishay Mansour, Vianney Perchet

ALT 2020 Cooperative Online Learning: Keeping Your Neighbors Updated Nicolò Cesa-Bianchi, Tommaso Cesari, Claire Monteleoni

NeurIPS 2020 Exact Recovery of Mangled Clusters with Same-Cluster Queries Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice

NeurIPS 2020 Locally-Adaptive Nonparametric Online Learning Ilja Kuzborskij, Nicolò Cesa-Bianchi

AISTATS 2020 Stochastic Bandits with Delay-Dependent Payoffs Leonardo Cella, Nicoló Cesa-Bianchi

NeurIPS 2019 Correlation Clustering with Adaptive Similarity Queries Marco Bressan, Nicolò Cesa-Bianchi, Andrea Paudice, Fabio Vitale

JMLR 2019 Delay and Cooperation in Nonstochastic Bandits Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

COLT 2019 Distribution-Dependent Analysis of Gibbs-ERM Principle Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári

ALT 2019 Dynamic Pricing with Finitely Many Unknown Valuations Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet

AISTATS 2019 Efficient Linear Bandits Through Matrix Sketching Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi

NeurIPS 2019 Nonstochastic Multiarmed Bandits with Unrestricted Delays Tobias Sommer Thune, Nicolò Cesa-Bianchi, Yevgeny Seldin

ALT 2018 Bandit Regret Scaling with the Effective Loss Range Nicolò Cesa-Bianchi, Ohad Shamir

COLT 2018 Nonstochastic Bandits with Composite Anonymous Feedback Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

COLT 2017 Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile, Sébastien Gerchinovitz

NeurIPS 2017 Boltzmann Exploration Done Right Nicolò Cesa-Bianchi, Claudio Gentile, Gabor Lugosi, Gergely Neu

JAIR 2017 Confidence Decision Trees via Online and Active Learning for Streaming Data Rocco De Rosa, Nicolò Cesa-Bianchi

NeurIPS 2017 Nonparametric Online Regression While Learning the Metric Ilja Kuzborskij, Nicolò Cesa-Bianchi

AISTATS 2017 On the Troll-Trust Model for Edge Sign Prediction in Social Networks Géraud Le Falher, Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale

COLT 2016 Delay and Cooperation in Nonstochastic Bandits Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour, Alberto Minora

NeurIPS 2016 Efficient Second Order Online Learning by Sketching Haipeng Luo, Alekh Agarwal, Nicolò Cesa-Bianchi, John Langford

MLJ 2015 A Generalized Online Mirror Descent with Applications to Classification and Regression Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi

COLT 2015 On the Complexity of Learning with Kernels Nicolò Cesa-Bianchi, Yishay Mansour, Ohad Shamir

COLT 2015 Online Learning with Feedback Graphs: Beyond Bandits Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren

NeurIPS 2013 A Gang of Bandits Nicolò Cesa-Bianchi, Claudio Gentile, Giovanni Zappella

NeurIPS 2013 From Bandits to Experts: A Tale of Domination and Independence Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

NeurIPS 2013 Online Learning with Switching Costs and Other Adaptive Adversaries Nicolò Cesa-Bianchi, Ofer Dekel, Ohad Shamir

JMLR 2013 Random Spanning Trees and the Prediction of Weighted Graphs Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

COLT 2013 Regret Minimization for Branching Experts Eyal Gofer, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour

COLT 2012 A Correlation Clustering Approach to Link Classification in Signed Networks Nicoló Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

NeurIPS 2012 A Linear Time Active Learning Algorithm for Link Classification Nicolò Cesa-bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

AISTATS 2012 Beyond Logarithmic Bounds in Online Learning Francesco Orabona, Nicolo Cesa-Bianchi, Claudio Gentile

NeurIPS 2012 Mirror Descent Meets Fixed Share (and Feels No Regret) Nicolò Cesa-bianchi, Pierre Gaillard, Gabor Lugosi, Gilles Stoltz

UAI 2012 PAC-Bayesian Inequalities for Martingales Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer

FnTML 2012 Regret Analysis of Stochastic and Nonstochastic Multi-Armed Bandit Problems Sébastien Bubeck, Nicolò Cesa-Bianchi

MLJ 2012 Synergy of Multi-Label Hierarchical Ensembles, Data Fusion, and Cost-Sensitive Methods for Gene Functional Inference Nicolò Cesa-Bianchi, Matteo Re, Giorgio Valentini

COLT 2012 Towards Minimax Policies for Online Linear Optimization with Bandit Feedback Sébastien Bubeck, Nicoló Cesa-Bianchi, Sham M. Kakade

ICML 2011 Better Algorithms for Selective Sampling Francesco Orabona, Nicolò Cesa-Bianchi

JMLR 2011 Efficient Learning with Partially Observed Attributes Nicoló Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir

NeurIPS 2011 Efficient Online Learning via Randomized Rounding Nicolò Cesa-bianchi, Ohad Shamir

MLJ 2011 Learning Noisy Linear Classifiers via Adaptive and Selective Sampling Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile

AAAI 2011 Quantity Makes Quality: Learning with Partial Views Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir

NeurIPS 2011 See the Tree Through the Lines: The Shazoo Algorithm Fabio Vitale, Nicolò Cesa-bianchi, Claudio Gentile, Giovanni Zappella

COLT 2010 Active Learning on Trees and Graphs Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

ICML 2010 Efficient Learning with Partially Observed Attributes Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir

MLJ 2010 Guest Editorial: Learning from Multiple Sources Nicolò Cesa-Bianchi, David R. Hardoon, Gayle Leen

JMLR 2010 Linear Algorithms for Online Multitask Classification Giovanni Cavallanti, Nicoló Cesa-Bianchi, Claudio Gentile

CVPRW 2010 OM-2: An Online Multi-Class Multi-Kernel Learning Algorithm Luo Jie Francesco Orabona, Marco Fornoni, Barbara Caputo, Nicolò Cesa-Bianchi

COLT 2010 Online Learning of Noisy Data with Kernels Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir

ICML 2010 Random Spanning Trees and the Prediction of Weighted Graphs Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

COLT 2009 Combinatorial Bandits Nicolò Cesa-Bianchi, Gábor Lugosi

COLT 2009 Fast and Optimal Prediction on a Labeled Tree Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale

ALT 2009 Learning Unknown Graphs Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale

ICML 2009 Robust Bounds for Classification via Selective Sampling Nicolò Cesa-Bianchi, Claudio Gentile, Francesco Orabona

COLT 2008 Linear Algorithms for Online Multitask Classification Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile

NeurIPS 2008 Linear Classification and Selective Sampling Under Low Noise Conditions Giovanni Cavallanti, Nicolò Cesa-bianchi, Claudio Gentile

MLJ 2007 Improved Second-Order Bounds for Prediction with Expert Advice Nicolò Cesa-Bianchi, Yishay Mansour, Gilles Stoltz

MLJ 2007 Tracking the Best Hyperplane with a Simple Budget Perceptron Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile

ICML 2006 Hierarchical Classification: Combining Bayes with SVM Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni

JMLR 2006 Incremental Algorithms for Hierarchical Classification Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni

COLT 2006 Tracking the Best Hyperplane with a Simple Budget Perceptron Nicolò Cesa-Bianchi, Claudio Gentile

JMLR 2006 Worst-Case Analysis of Selective Sampling for Linear Classification Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni

NeurIPS 2005 Improved Risk Tail Bounds for On-Line Algorithms Nicolò Cesa-bianchi, Claudio Gentile

COLT 2005 Improved Second-Order Bounds for Prediction with Expert Advice Nicolò Cesa-Bianchi, Yishay Mansour, Gilles Stoltz

ALT 2004 Applications of Regularized Least Squares to Classification Problems Nicolò Cesa-Bianchi

NeurIPS 2004 Incremental Algorithms for Hierarchical Classification Nicolò Cesa-bianchi, Claudio Gentile, Andrea Tironi, Luca Zaniboni

COLT 2004 Minimizing Regret with Label Efficient Prediction Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz

COLT 2004 Regret Bounds for Hierarchical Classification with Linear-Threshold Functions Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile

NeurIPS 2004 Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms Nicolò Cesa-bianchi, Claudio Gentile, Luca Zaniboni

COLT 2003 Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile

MLJ 2003 Potential-Based Algorithms in On-Line Prediction and Game Theory Nicolò Cesa-Bianchi, Gábor Lugosi

COLT 2002 A Second-Order Perceptron Algorithm Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile

ALT 2002 Algorithmic Learning Theory, 13th International Conference, ALT 2002, Lübeck, Germany, November 24-26, 2002, Proceedings Nicolò Cesa-Bianchi, Masayuki Numao, Rüdiger Reischuk

ALT 2002 Editors' Introduction Nicolò Cesa-Bianchi, Masayuki Numao, Rüdiger Reischuk

MLJ 2002 Finite-Time Analysis of the Multiarmed Bandit Problem Peter Auer, Nicolò Cesa-Bianchi, Paul Fischer

NeurIPS 2002 Margin-Based Algorithms for Information Filtering Nicolò Cesa-bianchi, Alex Conconi, Claudio Gentile

NeurIPS 2001 On the Generalization Ability of On-Line Learning Algorithms Nicolò Cesa-bianchi, Alex Conconi, Claudio Gentile

COLT 2001 Potential-Based Algorithms in Online Prediction and Game Theory Nicolò Cesa-Bianchi, Gábor Lugosi

MLJ 2001 Worst-Case Bounds for the Logarithmic Loss of Predictors Nicolò Cesa-Bianchi, Gábor Lugosi

COLT 2000 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28 - July 1, 2000, Palo Alto, California, USA Nicolò Cesa-Bianchi, Sally A. Goldman

MLJ 1999 Guest Editors' Introduction Jonathan Baxter, Nicolò Cesa-Bianchi

COLT 1999 Minimax Regret Under Log Loss for General Classes of Experts Nicolò Cesa-Bianchi, Gábor Lugosi

ICML 1998 Finite-Time Regret Bounds for the Multiarmed Bandit Problem Nicolò Cesa-Bianchi, Paul Fischer

COLT 1998 On Sequential Prediction of Individual Sequences Relative to a Set of Experts Nicolò Cesa-Bianchi, Gábor Lugosi

COLT 1997 Analysis of Two Gradient-Based Algorithms for On-Line Regression Nicolò Cesa-Bianchi

COLT 1996 On Bayes Methods for On-Line Boolean Prediction Nicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza

MLJ 1996 On-Line Prediction and Conversion Strategies Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth

ALT 1994 On-Line Learning with Malicious Noise and the Closure Algorithm Peter Auer, Nicolò Cesa-Bianchi

COLT 1993 Worst-Case Quadratic Loss Bounds for a Generalization of the Widrow-Hoff Rule Nicolò Cesa-Bianchi, Philip M. Long, Manfred K. Warmuth

COLT 1992 Characterizations of Learnability for Classes of O, ..., N-Valued Functions Shai Ben-David, Nicolò Cesa-Bianchi, Philip M. Long

ALT 1990 Learning the Distribution in the Extended PAC Model Nicolò Cesa-Bianchi