Nicolò Cesa-Bianchi

283 papers A* 70A 13B 11C 1Journal 156Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Perturbation Approach to Unconstrained Linear Bandits. CoRR Andrew Jacobsen, Dorian Baudry, Shinji Ito, Nicolò Cesa-Bianchi
2026	J	`jnl`	Learning Conditional Averages. CoRR Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
2026	J	`jnl`	Lookahead identification in adversarial bandits: accuracy and memory bounds. CoRR Nataly Brukhim, Nicolò Cesa-Bianchi, Carlo Ciliberto
2026	J	`jnl`	Near-Optimal Regret for Distributed Adversarial Bandits: A Black-Box Approach. CoRR Hao Qiu, Mengxiao Zhang, Nicolò Cesa-Bianchi
2026	A*	`conf`	Online Linear Regression with Paid Stochastic Features. AAAI Nadav Merlis, Kyoungseok Jang, Nicolò Cesa-Bianchi
2026	J	`jnl`	Parameter-Free Dynamic Regret for Unconstrained Linear Bandits. CoRR Alberto Rumi, Andrew Jacobsen, Nicolò Cesa-Bianchi, Fabio Vitale
2025	A*	`conf`	A Fine-grained Characterization of PAC Learnability. COLT Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
2025	J	`jnl`	A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. J. Mach. Learn. Res. Lukas Zierahn, Dirk van der Hoeven, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi
2025	J	`jnl`	Dynamic Regret Reduces to Kernelized Static Regret. CoRR Andrew Jacobsen, Alessandro Rudi, Francesco Orabona, Nicolò Cesa-Bianchi
2025	J	`jnl`	Improved Regret Bounds for Bandits with Expert Advice. J. Artif. Intell. Res. Nicolò Cesa-Bianchi, Khaled Eldowa, Emmanuel Esposito, Julia Olkhovskaya
2025	J	`jnl`	Instance-Dependent Regret Bounds for Nonstochastic Linear Partial Monitoring. CoRR Federico Di Gennaro, Khaled Eldowa, Nicolò Cesa-Bianchi
2025	A*	`conf`	Market Making without Regret. COLT Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Luigi Foscari, Vinayak Pathak
2025	A*	`conf`	Of Dice and Games: A Theory of Generalized Boosting. COLT Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
2025	J	`jnl`	Online Linear Regression with Paid Stochastic Features. CoRR Nadav Merlis, Kyoungseok Jang, Nicolò Cesa-Bianchi
2025	J	`jnl`	Stochastic Bandits for Crowdsourcing and Multi-Platform Autobidding. CoRR François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
2025	J	`jnl`	The Invisible Handshake: Tacit Collusion between Adaptive Market Agents. CoRR Luigi Foscari, Emanuele Guidotti, Nicolò Cesa-Bianchi, Tatjana Chavdarova, Alfio Ferrara
2024	A*	`conf`	A Theory of Interpretable Approximations. COLT Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
2024	J	`jnl`	A Theory of Interpretable Approximations. CoRR Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
2024	A	`conf`	Best-of-Both-Worlds Algorithms for Linear Contextual Bandits. AISTATS Yuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicolò Cesa-Bianchi
2024	J	`jnl`	Bilateral Trade: A Regret Minimization Perspective. Math. Oper. Res. Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2024	J	`jnl`	Cooperative Online Learning with Feedback Graphs. Trans. Mach. Learn. Res. Nicolò Cesa-Bianchi, Tommaso Cesari, Riccardo Della Vecchia
2024	J	`jnl`	Distributed Online Optimization with Stochastic Agent Availability. CoRR Juliette Achddou, Nicolò Cesa-Bianchi, Hao Qiu
2024	A*	`conf`	Fair Online Bilateral Trade. NeurIPS François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
2024	J	`jnl`	Fair Online Bilateral Trade. CoRR François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
2024	J	`jnl`	Improved Regret Bounds for Bandits with Expert Advice. CoRR Nicolò Cesa-Bianchi, Khaled Eldowa, Emmanuel Esposito, Julia Olkhovskaya
2024	J	`jnl`	Information Capacity Regret Bounds for Bandits with Mediator Feedback. CoRR Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli
2024	J	`jnl`	Information Capacity Regret Bounds for Bandits with Mediator Feedback. J. Mach. Learn. Res. Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli
2024	J	`jnl`	Linear Bandits with Memory. Trans. Mach. Learn. Res. Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi
2024	J	`jnl`	Margin-Based Active Learning of Classifiers. J. Mach. Learn. Res. Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2024	J	`jnl`	Market Making without Regret. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Luigi Foscari, Vinayak Pathak
2024	A	`conf`	Multitask Online Learning: Listen to the Neighborhood Buzz. AISTATS Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue
2024	J	`jnl`	Of Dice and Games: A Theory of Generalized Boosting. CoRR Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
2024	J	`jnl`	Regret Analysis of Bilateral Trade with a Smoothed Adversary. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2024	A*	`conf`	Sparsity-Agnostic Linear Bandits with Adaptive Adversaries. NeurIPS Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi
2024	J	`jnl`	Sparsity-Agnostic Linear Bandits with Adaptive Adversaries. CoRR Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi
2024	A	`conf`	Sum-max Submodular Bandits. AISTATS Stephen U. Pasteris, Alberto Rumi, Fabio Vitale, Nicolò Cesa-Bianchi
2024	A*	`conf`	The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations. STOC Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2023	A*	`conf`	A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. COLT Dirk van der Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi
2023	J	`jnl`	A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. CoRR Dirk van der Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi
2023	J	`jnl`	Adaptive maximization of social welfare. CoRR Nicolò Cesa-Bianchi, Roberto Colomboni, Maximilian Kasy
2023	J	`jnl`	Best-of-Both-Worlds Algorithms for Linear Contextual Bandits. CoRR Yuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicolò Cesa-Bianchi
2023	A*	`conf`	Delayed Bandits: When Do Intermediate Observations Help? ICML Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
2023	J	`jnl`	Delayed Bandits: When Do Intermediate Observations Help? CoRR Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
2023	J	`jnl`	High-Probability Risk Bounds via Sequential Predictors. CoRR Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
2023	B	`conf`	Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice. ITW Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli
2023	J	`jnl`	Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice. CoRR Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli
2023	A	`conf`	Learning the Stackelberg Equilibrium in a Newsvendor Game. AAMAS Nicolò Cesa-Bianchi, Tommaso Cesari, Takayuki Osogami, Marco Scarsini, Segev Wasserkrug
2023	J	`jnl`	Linear Bandits with Memory: from Rotting to Rising. CoRR Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi
2023	A*	`conf`	Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. NeurIPS Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
2023	J	`jnl`	Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. CoRR Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
2023	J	`jnl`	Multitask Online Learning: Listen to the Neighborhood Buzz. CoRR Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue
2023	A	`conf`	Nonstochastic Contextual Combinatorial Bandits. AISTATS Lukas Zierahn, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Gergely Neu
2023	A*	`conf`	On the Minimax Regret for Online Learning with Feedback Graphs. NeurIPS Khaled Eldowa, Emmanuel Esposito, Tommaso Cesari, Nicolò Cesa-Bianchi
2023	J	`jnl`	On the Minimax Regret for Online Learning with Feedback Graphs. CoRR Khaled Eldowa, Emmanuel Esposito, Tommaso Cesari, Nicolò Cesa-Bianchi
2023	A*	`conf`	Repeated Bilateral Trade Against a Smoothed Adversary. COLT Nicolò Cesa-Bianchi, Tommaso Renato Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2023	J	`jnl`	Repeated Bilateral Trade Against a Smoothed Adversary. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2023	J	`jnl`	Sum-max Submodular Bandits. CoRR Stephen Pasteris, Alberto Rumi, Fabio Vitale, Nicolò Cesa-Bianchi
2023	J	`jnl`	The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2023	A*	`conf`	Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts. ICML Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi
2023	J	`jnl`	Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts. CoRR Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi
2022	A	`conf`	A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits. AISTATS Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach
2022	A*	`conf`	A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs. NeurIPS Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
2022	J	`jnl`	A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs. CoRR Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
2022	A*	`conf`	A Regret-Variance Trade-Off in Online Learning. NeurIPS Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
2022	J	`jnl`	A Regret-Variance Trade-Off in Online Learning. CoRR Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
2022	A*	`conf`	Active Learning of Classifiers with Label and Seed Queries. NeurIPS Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen
2022	J	`jnl`	Active Learning of Classifiers with Label and Seed Queries. CoRR Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen
2022	A*	`conf`	Learning on the Edge: Online Learning with Stochastic Feedback Graphs. NeurIPS Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi
2022	J	`jnl`	Learning on the Edge: Online Learning with Stochastic Feedback Graphs. CoRR Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi
2022	J	`jnl`	Multitask Online Mirror Descent. Trans. Mach. Learn. Res. Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil
2022	A	`conf`	Nonstochastic Bandits and Experts with Arm-Dependent Delays. AISTATS Dirk van der Hoeven, Nicolò Cesa-Bianchi
2022	J	`jnl`	Nonstochastic Bandits with Composite Anonymous Feedback. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour
2022	J	`jnl`	Online Learning in Supply-Chain Games. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Takayuki Osogami, Marco Scarsini, Segev Wasserkrug
2021	A*	`conf`	A New Theoretical Framework for Fast and Accurate Online Decision-Making. NeurIPS Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet
2021	A*	`conf`	A Regret Analysis of Bilateral Trade. EC Nicolò Cesa-Bianchi, Tommaso Renato Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2021	J	`jnl`	A Regret Analysis of Bilateral Trade. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2021	A*	`conf`	An Algorithm for Stochastic and Adversarial Bandits with Switching Costs. ICML Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
2021	J	`jnl`	An Algorithm for Stochastic and Adversarial Bandits with Switching Costs. CoRR Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
2021	A*	`conf`	Beyond Bandit Feedback in Online Multiclass Classification. NeurIPS Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi
2021	J	`jnl`	Beyond Bandit Feedback in Online Multiclass Classification. CoRR Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi
2021	J	`jnl`	Bilateral Trade: A Regret Minimization Perspective. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2021	J	`jnl`	Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality. CoRR Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach
2021	J	`jnl`	Cooperative Online Learning with Feedback Graphs. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Riccardo Della Vecchia
2021	A*	`conf`	Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. COLT Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2021	J	`jnl`	Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. CoRR Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2021	J	`jnl`	Multi-Sided Matching Markets with Consistent Preferences and Cooperative Partners. CoRR Maximilian Mordig, Riccardo Della Vecchia, Nicolò Cesa-Bianchi, Bernhard Schölkopf
2021	J	`jnl`	Multitask Online Mirror Descent. CoRR Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil
2021	J	`jnl`	Nonstochastic Bandits and Experts with Arm-Dependent Delays. CoRR Dirk van der Hoeven, Nicolò Cesa-Bianchi
2021	J	`jnl`	Nonstochastic Bandits with Composite Anonymous Feedback. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour
2021	A*	`conf`	On Margin-Based Cluster Recovery with Oracle Queries. NeurIPS Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2021	J	`jnl`	On Margin-Based Cluster Recovery with Oracle Queries. CoRR Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2020	B	`conf`	Cooperative Online Learning: Keeping your Neighbors Updated. ALT Nicolò Cesa-Bianchi, Tommaso Cesari, Claire Monteleoni
2020	A*	`conf`	Exact Recovery of Mangled Clusters with Same-Cluster Queries. NeurIPS Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2020	J	`jnl`	Exact Recovery of Mangled Clusters with Same-Cluster Queries. CoRR Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
2020	A*	`conf`	Locally-Adaptive Nonparametric Online Learning. NeurIPS Ilja Kuzborskij, Nicolò Cesa-Bianchi
2020	J	`jnl`	Locally-Adaptive Nonparametric Online Learning. CoRR Ilja Kuzborskij, Nicolò Cesa-Bianchi
2020	A	`conf`	Stochastic Bandits with Delay-Dependent Payoffs. AISTATS Leonardo Cella, Nicolò Cesa-Bianchi
2019	J	`jnl`	Cooperative Online Learning: Keeping your Neighbors Updated. CoRR Nicolò Cesa-Bianchi, Tommaso Renato Cesari, Claire Monteleoni
2019	A*	`conf`	Correlation Clustering with Adaptive Similarity Queries. NeurIPS Marco Bressan, Nicolò Cesa-Bianchi, Andrea Paudice, Fabio Vitale
2019	J	`jnl`	Correlation Clustering with Adaptive Similarity Queries. CoRR Marco Bressan, Nicolò Cesa-Bianchi, Andrea Paudice, Fabio Vitale
2019	J	`jnl`	Delay and Cooperation in Nonstochastic Bandits. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2019	A*	`conf`	Distribution-Dependent Analysis of Gibbs-ERM Principle. COLT Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári
2019	J	`jnl`	Distribution-Dependent Analysis of Gibbs-ERM Principle. CoRR Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári
2019	B	`conf`	Dynamic Pricing with Finitely Many Unknown Valuations. ALT Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet
2019	A	`conf`	Efficient Linear Bandits through Matrix Sketching. AISTATS Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
2019	J	`jnl`	Multitask Protein Function Prediction through Task Dissimilarity. IEEE ACM Trans. Comput. Biol. Bioinform. Marco Frasca, Nicolò Cesa-Bianchi
2019	A*	`conf`	Nonstochastic Multiarmed Bandits with Unrestricted Delays. NeurIPS Tobias Sommer Thune, Nicolò Cesa-Bianchi, Yevgeny Seldin
2019	J	`jnl`	Nonstochastic Multiarmed Bandits with Unrestricted Delays. CoRR Tobias Sommer Thune, Nicolò Cesa-Bianchi, Yevgeny Seldin
2019	J	`jnl`	Repeated A/B Testing. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet
2019	J	`jnl`	Stochastic Bandits with Delay-Dependent Payoffs. CoRR Leonardo Cella, Nicolò Cesa-Bianchi
2018	A*	`ed.`	Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada. NeurIPS Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett
2018	B	`conf`	Bandit Regret Scaling with the Effective Loss Range. ALT Nicolò Cesa-Bianchi, Ohad Shamir
2018	J	`jnl`	Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction. CoRR Marco Frasca, Nicolò Cesa-Bianchi
2018	J	`jnl`	Dynamic Pricing with Finitely Many Unknown Valuations. CoRR Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet
2018	J	`jnl`	Efficient Linear Bandits through Matrix Sketching. CoRR Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
2018	A*	`conf`	Nonstochastic Bandits with Composite Anonymous Feedback. COLT Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2017	J	`jnl`	Active Incremental Recognition of Human Activities in a Streaming Context. Pattern Recognit. Lett. Rocco De Rosa, Ilaria Gori, Fabio Cuzzolin, Nicolò Cesa-Bianchi
2017	A*	`conf`	Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning. COLT Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile, Sébastien Gerchinovitz
2017	J	`jnl`	Bandit Regret Scaling with the Effective Loss Range. CoRR Nicolò Cesa-Bianchi, Ohad Shamir
2017	—	`conf`	Boltzmann Exploration Done Right. NIPS Nicolò Cesa-Bianchi, Claudio Gentile, Gergely Neu, Gábor Lugosi
2017	J	`jnl`	Boltzmann Exploration Done Right. CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Gábor Lugosi, Gergely Neu
2017	J	`jnl`	Confidence Decision Trees via Online and Active Learning for Streaming Data. J. Artif. Intell. Res. Rocco De Rosa, Nicolò Cesa-Bianchi
2017	—	`conf`	Nonparametric Online Regression while Learning the Metric. NIPS Ilja Kuzborskij, Nicolò Cesa-Bianchi
2017	J	`jnl`	Nonparametric Online Regression while Learning the Metric. CoRR Ilja Kuzborskij, Nicolò Cesa-Bianchi
2017	J	`jnl`	Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback. SIAM J. Comput. Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Shie Mannor, Yishay Mansour, Ohad Shamir
2017	A	`conf`	On the Troll-Trust Model for Edge Sign Prediction in Social Networks. AISTATS Géraud Le Falher, Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale
2017	J	`jnl`	Online Nonparametric Learning, Chaining, and the Role of Partial Feedback. CoRR Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile, Sébastien Gerchinovitz
2016	J	`jnl`	Active Learning for Online Recognition of Human Activities from Streaming Videos. CoRR Rocco De Rosa, Ilaria Gori, Fabio Cuzzolin, Barbara Caputo, Nicolò Cesa-Bianchi
2016	A*	`conf`	Delay and Cooperation in Nonstochastic Bandits. COLT Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour, Alberto Minora
2016	J	`jnl`	Delay and Cooperation in Nonstochastic Bandits. CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour, Alberto Minora
2016	—	`conf`	Efficient Second Order Online Learning by Sketching. NIPS Haipeng Luo, Alekh Agarwal, Nicolò Cesa-Bianchi, John Langford
2016	J	`jnl`	Efficient Second Order Online Learning via Sketching. CoRR Haipeng Luo, Alekh Agarwal, Nicolò Cesa-Bianchi, John Langford
2016	—	`ch.`	Multi-armed Bandit Problem. Encyclopedia of Algorithms Nicolò Cesa-Bianchi
2016	J	`jnl`	Multitask Protein Function Prediction Through Task Dissimilarity. CoRR Marco Frasca, Nicolò Cesa-Bianchi
2016	J	`jnl`	On the Troll-Trust Model for Edge Sign Prediction in Social Networks. CoRR Géraud Le Falher, Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale
2015	J	`jnl`	A generalized online mirror descent with applications to classification and regression. Mach. Learn. Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi
2015	A*	`conf`	On the Complexity of Learning with Kernels. COLT Nicolò Cesa-Bianchi, Yishay Mansour, Ohad Shamir
2015	A*	`conf`	Online Learning with Feedback Graphs: Beyond Bandits. COLT Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren
2015	J	`jnl`	Online Learning with Feedback Graphs: Beyond Bandits. CoRR Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren
2015	J	`jnl`	Regret Minimization for Reserve Prices in Second-Price Auctions. IEEE Trans. Inf. Theory Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2015	B	`conf`	Splitting with confidence in decision trees with application to stream mining. IJCNN Rocco De Rosa, Nicolò Cesa-Bianchi
2015	A*	`conf`	The ABACOC Algorithm: A Novel Approach for Nonparametric Classification of Data Streams. ICDM Rocco De Rosa, Francesco Orabona, Nicolò Cesa-Bianchi
2015	J	`jnl`	The ABACOC Algorithm: a Novel Approach for Nonparametric Classification of Data Streams. CoRR Rocco De Rosa, Francesco Orabona, Nicolò Cesa-Bianchi
2014	J	`jnl`	Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback. CoRR Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Shie Mannor, Yishay Mansour, Ohad Shamir
2014	J	`jnl`	On the Complexity of Learning with Kernels. CoRR Nicolò Cesa-Bianchi, Yishay Mansour, Ohad Shamir
2014	A	`conf`	Online Action Recognition via Nonparametric Incremental Learning. BMVC Rocco De Rosa, Nicolò Cesa-Bianchi, Ilaria Gori, Fabio Cuzzolin
2013	J	`jnl`	A Correlation Clustering Approach to Link Classification in Signed Networks CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2013	—	`conf`	A Gang of Bandits. NIPS Nicolò Cesa-Bianchi, Claudio Gentile, Giovanni Zappella
2013	J	`jnl`	A Gang of Bandits. CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Giovanni Zappella
2013	J	`jnl`	A Generalized Online Mirror Descent with Applications to Classification and Regression CoRR Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi
2013	J	`jnl`	A Linear Time Active Learning Algorithm for Link Classification CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2013	J	`jnl`	Active Learning on Trees and Graphs CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2013	J	`jnl`	Bandits With Heavy Tail. IEEE Trans. Inf. Theory Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
2013	—	`conf`	Efficient Transductive Online Learning via Randomized Rounding. Empirical Inference Nicolò Cesa-Bianchi, Ohad Shamir
2013	—	`conf`	From Bandits to Experts: A Tale of Domination and Independence. NIPS Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2013	J	`jnl`	From Bandits to Experts: A Tale of Domination and Independence. CoRR Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2013	J	`jnl`	Online Learning with Switching Costs and Other Adaptive Adversaries CoRR Nicolò Cesa-Bianchi, Ofer Dekel, Ohad Shamir
2013	—	`conf`	Online Learning with Switching Costs and Other Adaptive Adversaries. NIPS Nicolò Cesa-Bianchi, Ofer Dekel, Ohad Shamir
2013	J	`jnl`	Random spanning trees and the prediction ofweighted graphs. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2013	A*	`conf`	Regret Minimization for Branching Experts. COLT Eyal Gofer, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2013	A*	`conf`	Regret Minimization for Reserve Prices in Second-Price Auctions. SODA Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour
2013	J	`jnl`	See the Tree Through the Lines: The Shazoo Algorithm CoRR Fabio Vitale, Nicolò Cesa-Bianchi, Claudio Gentile, Giovanni Zappella
2012	A*	`conf`	A Correlation Clustering Approach to Link Classification in Signed Networks. COLT Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2012	—	`conf`	A Linear Time Active Learning Algorithm for Link Classification. NIPS Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2012	J	`jnl`	A new look at shifting regret CoRR Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz
2012	J	`jnl`	Bandits with heavy tail CoRR Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
2012	A	`conf`	Beyond Logarithmic Bounds in Online Learning. AISTATS Francesco Orabona, Nicolò Cesa-Bianchi, Claudio Gentile
2012	J	`jnl`	Combinatorial bandits. J. Comput. Syst. Sci. Nicolò Cesa-Bianchi, Gábor Lugosi
2012	J	`jnl`	Memory Constraint Online Multitask Classification CoRR Giovanni Cavallanti, Nicolò Cesa-Bianchi
2012	—	`conf`	Mirror Descent Meets Fixed Share (and feels no regret). NIPS Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz
2012	—	`conf`	PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits. ICML On-line Trading of Exploration and Exploitation Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter Auer, François Laviolette, John Shawe-Taylor
2012	A	`conf`	PAC-Bayesian Inequalities for Martingales. UAI Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer
2012	J	`jnl`	PAC-Bayesian Inequalities for Martingales. IEEE Trans. Inf. Theory Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer
2012	J	`jnl`	Random Spanning Trees and the Prediction of Weighted Graphs CoRR Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2012	J	`jnl`	Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems CoRR Sébastien Bubeck, Nicolò Cesa-Bianchi
2012	J	`jnl`	Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems. Found. Trends Mach. Learn. Sébastien Bubeck, Nicolò Cesa-Bianchi
2012	J	`jnl`	Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference. Mach. Learn. Nicolò Cesa-Bianchi, Matteo Re, Giorgio Valentini
2012	A*	`conf`	Towards Minimax Policies for Online Linear Optimization with Bandit Feedback. COLT Sébastien Bubeck, Nicolò Cesa-Bianchi, Sham M. Kakade
2012	J	`jnl`	Towards minimax policies for online linear optimization with bandit feedback CoRR Sébastien Bubeck, Nicolò Cesa-Bianchi, Sham M. Kakade
2011	A*	`conf`	Better Algorithms for Selective Sampling. ICML Francesco Orabona, Nicolò Cesa-Bianchi
2011	J	`jnl`	Efficient Learning with Partially Observed Attributes. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2011	J	`jnl`	Efficient Online Learning via Randomized Rounding CoRR Nicolò Cesa-Bianchi, Ohad Shamir
2011	—	`conf`	Efficient Online Learning via Randomized Rounding. NIPS Nicolò Cesa-Bianchi, Ohad Shamir
2011	—	`conf`	Ensembles and Multiple Classifiers: A Game-Theoretic View. MCS Nicolò Cesa-Bianchi
2011	J	`jnl`	Learning noisy linear classifiers via adaptive and selective sampling. Mach. Learn. Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile
2011	J	`jnl`	Online Learning of Noisy Data. IEEE Trans. Inf. Theory Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2011	J	`jnl`	PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits CoRR Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter Auer, François Laviolette, John Shawe-Taylor
2011	J	`jnl`	PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off CoRR Yevgeny Seldin, Nicolò Cesa-Bianchi, François Laviolette, Peter Auer, John Shawe-Taylor, Jan Peters
2011	J	`jnl`	PAC-Bayesian Inequalities for Martingales CoRR Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer
2011	J	`jnl`	Predicting the labels of an unknown graph via adaptive exploration. Theor. Comput. Sci. Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale
2011	A*	`conf`	Quantity Makes Quality: Learning with Partial Views. AAAI Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2011	—	`conf`	See the Tree Through the Lines: The Shazoo Algorithm. NIPS Fabio Vitale, Nicolò Cesa-Bianchi, Claudio Gentile, Giovanni Zappella
2011	—	`conf`	The Game-Theoretic Approach to Machine Learning and Adaptation. ICAIS Nicolò Cesa-Bianchi
2010	A*	`conf`	Active Learning on Trees and Graphs. COLT Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2010	J	`jnl`	Efficient Learning with Partially Observed Attributes CoRR Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2010	A*	`conf`	Efficient Learning with Partially Observed Attributes. ICML Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2010	J	`jnl`	Guest Editorial: Learning from multiple sources. Mach. Learn. Nicolò Cesa-Bianchi, David R. Hardoon, Gayle Leen
2010	—	`conf`	Hierarchical Cost-Sensitive Algorithms for Genome-Wide Gene Function Prediction. MLSB Nicolò Cesa-Bianchi, Giorgio Valentini
2010	J	`jnl`	Linear Algorithms for Online Multitask Classification. J. Mach. Learn. Res. Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile
2010	—	`conf`	OM-2: An online multi-class Multi-Kernel Learning algorithm Luo Jie. CVPR Workshops Francesco Orabona, Marco Fornoni, Barbara Caputo, Nicolò Cesa-Bianchi
2010	J	`jnl`	Online Learning of Noisy Data with Kernels CoRR Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2010	A*	`conf`	Online Learning of Noisy Data with Kernels. COLT Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
2010	A*	`conf`	Random Spanning Trees and the Prediction of Weighted Graphs. ICML Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
2009	A*	`conf`	Combinatorial Bandits. COLT Nicolò Cesa-Bianchi, Gábor Lugosi
2009	A*	`conf`	Fast and Optimal Prediction on a Labeled Tree. COLT Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale
2009	B	`conf`	Learning Unknown Graphs. ALT Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale
2009	C	`conf`	Online discriminative learning: theory and applications. ASRU Nicolò Cesa-Bianchi
2009	—	`conf`	Online learning for CAT applications. SMART@EAMT Nicolò Cesa-Bianchi, Gabriele Reverberi
2009	A*	`conf`	Robust bounds for classification via selective sampling. ICML Nicolò Cesa-Bianchi, Claudio Gentile, Francesco Orabona
2008	J	`jnl`	HCGene: a software tool to support the hierarchical classification of genes. Bioinform. Giorgio Valentini, Nicolò Cesa-Bianchi
2008	J	`jnl`	Improved Risk Tail Bounds for On-Line Algorithms. IEEE Trans. Inf. Theory Nicolò Cesa-Bianchi, Claudio Gentile
2008	A*	`conf`	Linear Algorithms for Online Multitask Classification. COLT Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile
2008	—	`conf`	Linear Classification and Selective Sampling Under Low Noise Conditions. NIPS Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile
2007	J	`jnl`	Applications of regularized least squares to pattern classification. Theor. Comput. Sci. Nicolò Cesa-Bianchi
2007	J	`jnl`	Improved second-order bounds for prediction with expert advice. Mach. Learn. Nicolò Cesa-Bianchi, Yishay Mansour, Gilles Stoltz
2007	J	`jnl`	Tracking the best hyperplane with a simple budget Perceptron. Mach. Learn. Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile
2006	J	`jnl`	A distributed voting scheme to maximize preferences. RAIRO Theor. Informatics Appl. Peter Auer, Nicolò Cesa-Bianchi
2006	J	`jnl`	Foreword. Theor. Comput. Sci. Nicolò Cesa-Bianchi, Rüdiger Reischuk, Thomas Zeugmann
2006	A*	`conf`	Hierarchical classification: combining Bayes with SVM. ICML Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
2006	J	`jnl`	Incremental Algorithms for Hierarchical Classification. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
2006	—	`book`	Prediction, learning, and games. Nicolò Cesa-Bianchi, Gábor Lugosi
2006	B	`conf`	Regret Minimization Under Partial Monitoring. ITW Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz
2006	J	`jnl`	Regret Minimization Under Partial Monitoring. Math. Oper. Res. Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz
2006	A*	`conf`	Tracking the Best Hyperplane with a Simple Budget Perceptron. COLT Nicolò Cesa-Bianchi, Claudio Gentile
2006	J	`jnl`	Worst-Case Analysis of Selective Sampling for Linear Classification. J. Mach. Learn. Res. Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
2005	—	`conf`	A Distributed Architecture for Management and Retrieval of Extended Points of Interest. ICDCS Workshops Claudio Bettini, Nicolò Cesa-Bianchi, Daniele Riboni
2005	J	`jnl`	A Second-Order Perceptron Algorithm. SIAM J. Comput. Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2005	A*	`conf`	Improved Second-Order Bounds for Prediction with Expert Advice. COLT Nicolò Cesa-Bianchi, Yishay Mansour, Gilles Stoltz
2005	—	`conf`	Improved risk tail bounds for on-line algorithms. NIPS Nicolò Cesa-Bianchi, Claudio Gentile
2005	J	`jnl`	Minimizing regret with label efficient prediction. IEEE Trans. Inf. Theory Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz
2004	B	`conf`	Applications of Regularized Least Squares to Classification Problems. ALT Nicolò Cesa-Bianchi
2004	—	`conf`	Incremental Algorithms for Hierarchical Classification. NIPS Nicolò Cesa-Bianchi, Claudio Gentile, Andrea Tironi, Luca Zaniboni
2004	A*	`conf`	Minimizing Regret with Label Efficient Prediction. COLT Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz
2004	J	`jnl`	On the Generalization Ability of On-Line Learning Algorithms. IEEE Trans. Inf. Theory Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2004	A*	`conf`	Regret Bounds for Hierarchical Classification with Linear-Threshold Functions. COLT Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2004	—	`conf`	Towards Highly Adaptive Services for Mobile Computing. MOBIS Alessandra Agostini, Claudio Bettini, Nicolò Cesa-Bianchi, Dario Maggiorini, Daniele Riboni, Michele Ruberl, Cristiano Sala, Davide Vitali
2004	—	`conf`	Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms. NIPS Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
2003	A*	`conf`	Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling. COLT Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2003	J	`jnl`	Potential-Based Algorithms in On-Line Prediction and Game Theory. Mach. Learn. Nicolò Cesa-Bianchi, Gábor Lugosi
2002	A*	`conf`	A Second-Order Perceptron Algorithm. COLT Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2002	J	`jnl`	Adaptive and Self-Confident On-Line Learning Algorithms. J. Comput. Syst. Sci. Peter Auer, Nicolò Cesa-Bianchi, Claudio Gentile
2002	B	`ed.`	Algorithmic Learning Theory, 13th International Conference, ALT 2002, Lübeck, Germany, November 24-26, 2002, Proceedings ALT Nicolò Cesa-Bianchi, Masayuki Numao, Rüdiger Reischuk
2002	B	`conf`	Editors' Introduction. ALT Nicolò Cesa-Bianchi, Masayuki Numao, Rüdiger Reischuk
2002	J	`jnl`	Finite-time Analysis of the Multiarmed Bandit Problem. Mach. Learn. Peter Auer, Nicolò Cesa-Bianchi, Paul Fischer
2002	—	`conf`	Kernel Methods for Document Filtering. TREC Nicola Cancedda, Cyril Goutte, Jean-Michel Renders, Nicolò Cesa-Bianchi, Alex Conconi, Yaoyong Li, John Shawe-Taylor, Alexei Vinokourov, Thore Graepel, Claudio Gentile
2002	—	`conf`	Margin-Based Algorithms for Information Filtering. NIPS Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2002	J	`jnl`	The Nonstochastic Multiarmed Bandit Problem. SIAM J. Comput. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
2001	—	`conf`	On the Generalization Ability of On-Line Learning Algorithms. NIPS Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile
2001	—	`conf`	Potential-Based Algorithms in Online Prediction and Game Theory. COLT/EuroCOLT Nicolò Cesa-Bianchi, Gábor Lugosi
2001	J	`jnl`	Worst-Case Bounds for the Logarithmic Loss of Predictors. Mach. Learn. Nicolò Cesa-Bianchi, Gábor Lugosi
2000	J	`jnl`	Gambling in a rigged casino: The adversarial multi-armed bandit problem Electron. Colloquium Comput. Complex. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
2000	J	`jnl`	On-line Learning with Malicious Noise and the Closure Algorithm Electron. Colloquium Comput. Complex. Peter Auer, Nicolò Cesa-Bianchi
2000	A*	`ed.`	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
1999	J	`jnl`	Analysis of Two Gradient-Based Algorithms for On-Line Regression. J. Comput. Syst. Sci. Nicolò Cesa-Bianchi
1999	J	`jnl`	Guest Editors' Introduction. Mach. Learn. Jonathan Baxter, Nicolò Cesa-Bianchi
1999	A*	`conf`	Minimax Regret Under log Loss for General Classes of Experts. COLT Nicolò Cesa-Bianchi, Gábor Lugosi
1999	J	`jnl`	Sample-Efficient Strategies for Learning in the Presence of Noise. J. ACM Nicolò Cesa-Bianchi, Eli Dichterman, Paul Fischer, Eli Shamir, Hans Ulrich Simon
1998	J	`jnl`	A Graph-theoretic Generalization of the Sauer-Shelah Lemma. Discret. Appl. Math. Nicolò Cesa-Bianchi, David Haussler
1998	A*	`conf`	Finite-Time Regret Bounds for the Multiarmed Bandit Problem. ICML Nicolò Cesa-Bianchi, Paul Fischer
1998	J	`jnl`	On Bayes Methods for On-Line Boolean Prediction. Algorithmica Nicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza
1998	A*	`conf`	On Sequential Prediction of Individual Sequences Relative to a Set of Experts. COLT Nicolò Cesa-Bianchi, Gábor Lugosi
1998	J	`jnl`	On-Line Learning with Malicious Noise and the Closure Algorithm. Ann. Math. Artif. Intell. Peter Auer, Nicolò Cesa-Bianchi
1997	A*	`conf`	Analysis of Two Gradient-based Algorithms for On-line Regression. COLT Nicolò Cesa-Bianchi
1997	J	`jnl`	How to use expert advice. J. ACM Nicolò Cesa-Bianchi, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, Manfred K. Warmuth
1997	—	`conf`	Randomized Hypotheses and Minimum Disagreement Hypotheses for Learning with Noise. EuroCOLT Nicolò Cesa-Bianchi, Paul Fischer, Eli Shamir, Hans Ulrich Simon
1997	J	`jnl`	Scale-sensitive dimensions, uniform convergence, and learnability. J. ACM Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler
1996	A*	`conf`	Noise-Tolerant Learning Near the Information-Theoretic Bound. STOC Nicolò Cesa-Bianchi, Eli Dichterman, Paul Fischer, Hans Ulrich Simon
1996	A*	`conf`	On Bayes Methods for On-Line Boolean Prediction. COLT Nicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza
1996	J	`jnl`	On-line Prediction and Conversion Strategies. Mach. Learn. Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth
1996	A*	`conf`	Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract). PODC Peter Auer, Pasquale Caianiello, Nicolò Cesa-Bianchi
1996	J	`jnl`	Worst-case quadratic loss bounds for prediction using linear functions and gradient descent. IEEE Trans. Neural Networks Nicolò Cesa-Bianchi, Philip M. Long, Manfred K. Warmuth
1995	J	`jnl`	Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions. J. Comput. Syst. Sci. Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler, Philip M. Long
1995	J	`jnl`	Efficient Learning with Equivalence Queries of Conjunctions of Modulo Functions. Inf. Process. Lett. Alberto Bertoni, Nicolò Cesa-Bianchi, Guido Fiorino
1995	A*	`conf`	Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem. FOCS Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
1994	J	`jnl`	Bounds on approximate steepest descent for likelihood maximization in exponential families. IEEE Trans. Inf. Theory Nicolò Cesa-Bianchi, Anders Krogh, Manfred K. Warmuth
1994	—	`conf`	On-line Learning with Malicious Noise and the Closure Algorithm. AII/ALT Peter Auer, Nicolò Cesa-Bianchi
1993	A*	`conf`	How to use expert advice. STOC Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, Manfred K. Warmuth
1993	—	`conf`	On-line prediction and conversion strategies. EuroCOLT Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth
1993	A*	`conf`	Scale-sensitive Dimensions, Uniform Convergence, and Learnability FOCS Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler
1993	A*	`conf`	Worst-Case Quadratic Loss Bounds for a Generalization of the Widrow-Hoff Rule. COLT Nicolò Cesa-Bianchi, Philip M. Long, Manfred K. Warmuth
1992	A*	`conf`	Characterizations of Learnability for Classes of { COLT Shai Ben-David, Nicolò Cesa-Bianchi, Philip M. Long
1990	B	`conf`	Learning the Distribution in the Extended PAC Model. ALT Nicolò Cesa-Bianchi
1988	J	`jnl`	Microcanonical annealing on neural networks. Neural Networks Gianpiero Cattaneo, Nicolò Cesa-Bianchi