Nicolò Cesa-Bianchi - Selected papers

nicolò cesa-bianchi - selected papers

"These scientific products take of course some time to fructuate." - V. Nabokov

Multi-Agent Online Learning

N. Cesa-Bianchi, T. Cesari, and R. Della Vecchia.
Cooperative online learning with feedback graphs.
Transactions on Machine Learning Research, 2024.
J. Achddou, N. Cesa-Bianchi, and P. Laforgue
Multitask online learning: listen to the neighborhood buzz
Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
P.G. Sessa, P. Laforgue, N. Cesa-Bianchi, and A. Krause
Multitask learning with no regret: from improved confidence bounds to active learning
Advances in Neural Information Processing Systems 36 (NeurIPS), 2023.
N. Cesa-Bianchi, P. Laforgue, A. Paudice, and M. Pontil
Multitask online mirror descent
Transactions on Machine Learning Research, 2022.
N. Cesa-Bianchi, T. Cesari, C. Monteleoni
Cooperative online learning: keeping your neighbors updated
Proceedings of the 31st International Conference on Algorithmic Learning Theory (ALT 2020). PMLR, 117:234-250, 2020.
N. Cesa-Bianchi, C. Gentile, and Y. Mansour
Delay and cooperation in nonstochastic bandits
Journal of Machine Learning Research. JMLR, 20(17):1-38, 2019.

Active Learning and Clustering with Queries

M. Bressan, N. Cesa-Bianchi, S. Lattanzi, and A. Paudice
Margin-based active learning of classifiers
Journal of Machine Learning Research. 25(127):1-45, 2024.
M. Bressan, N. Cesa-Bianchi, S. Lattanzi, A. Paudice, and M. Thiessen
Active learning of classifiers with label and seed queries
Advances in Neural Information Processing Systems 35 (NeurIPS), 2022.
M. Bressan, N. Cesa-Bianchi, S. Lattanzi, and A. Paudice
On margin-based cluster recovery with oracle queries
Advances in Neural Information Processing Systems 34 (NeurIPS), 2021.
M. Bressan, N. Cesa-Bianchi, S. Lattanzi, and A. Paudice
Exact recovery of clusters in finite metric spaces using oracle queries
Proceedings of the 34th Annual Conference on Learning Theory (COLT). PMLR 134:775-803, 2021.
M. Bressan, N. Cesa-Bianchi, S. Lattanzi, and A. Paudice
Exact recovery of mangled clusters with same-cluster queries
Advances in Neural Information Processing Systems 33 (NeurIPS), 2020 (oral presentation).
M. Bressan, N. Cesa-Bianchi, A. Paudice, and F. Vitale
Correlation clustering with adaptive similarity queries
Advances in Neural Information Processing Systems 32 (NeurIPS), 2019.

Bandits and Digital Markets

N. Cesa-Bianchi, R. Colomboni, and M. Kasy.
Adaptive maximization of social welfare
Econometrica, 93(3):1073-1104, 2025.
F. Bachoc, N. Cesa-Bianchi, T. Cesari, and R. Colomboni.
Fair online bilateral trade
Advances in Neural Information Processing Systems 37 (NeurIPS), 2024.
N. Cesa-Bianchi, T. Cesari, R. Colomboni, F. Fusco, and S. Leonardi.
Regret analysis of bilateral trade with a smoothed adversary
Journal of Machine Learning Research, 25(234):1-36, 2024.
N. Cesa-Bianchi, T. Cesari, R. Colomboni, F. Fusco, and S. Leonardi.
The role of transparency in repeated first-price auctions with unknown valuations.
56th Annual ACM Symposium on Theory of Computing (STOC), 2024.
N. Cesa-Bianchi, T. Cesari, R. Colomboni, F. Fusco, and S. Leonardi
Bilateral trade: A regret minimization perspective
Mathematics of Operations Research, 49(1):171-203, 2024.
N. Cesa-Bianchi, T. Cesari, T. Osogami, M. Scarsini, and S. Wasserkrug
Learning the Stackelberg equilibrium in a newsvendor game
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Pages 242-250, 2023.
N. Cesa-Bianchi, T. Cesari, and V. Perchet
Dynamic pricing with finitely many unknown valuations
Proceedings of the 30th International Conference on Algorithmic Learning Theory (ALT). PMLR, 98:247-273, 2019.
N. Cesa-Bianchi, C. Gentile, and Y. Mansour
Regret minimization for reserve prices in second-price auctions
IEEE Transactions on Information Theory, 61(1):549-564, 2015.

Multi-Armed Bandits

T. Jin, K. Jang, and N. Cesa-Bianchi.
Sparsity-agnostic linear bandits with adaptive adversaries
Advances in Neural Information Processing Systems 37 (NeurIPS), 2024.
K. Eldowa, N. Cesa-Bianchi, A. Metelli, and M. Restelli
Information capacity regret bounds for bandits with mediator feedback
Journal of Machine Learning Research. JMLR, 25(353):1-36, 2024.
G. Clerici, P. Laforgue, and N. Cesa-Bianchi.
Linear bandits with memory
Transactions on Machine Learning Research (featured paper), 2024.
Y. Kuroki, A. Rumi, T. Tsuchiya, F. Vitale, and N. Cesa-Bianchi.
Best-of-both-worlds algorithms for linear contextual bandits
Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
S. Pasteris, A. Rumi, F. Vitale, and N. Cesa-Bianchi.
Sum-max submodular bandits
Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
K. Eldowa, E. Esposito, T. Cesari, and N. Cesa-Bianchi
On the minimax regret for online learning with feedback graphs
Advances in Neural Information Processing Systems 36 (NeurIPS), 2023.
D. van der Hoeven, L. Zierahn, T. Lancewicki, A. Rosenberg, and N. Cesa-Bianchi
A unified analysis of nonstochastic delayed feedback for combinatorial semi-bandits, linear bandits, and MDPs
Proceedings of the 36th Annual Conference on Learning Theory (COLT). PMLR 195:1285-1321, 2023.
E. Esposito, S. Masoudian, H. Qiu, D. van der Hoeven, N. Cesa-Bianchi, and Y. Seldin
Delayed bandits: when do intermediate observations help?
Proceedings of the 40th International Conference on Machine Learning (ICML). PMLR 202:9374-9395, 2023.
D. van der Hoeven, C. Pike-Burke, H. Qiu, and N. Cesa-Bianchi
Trading-off payments and accuracy in online classification with paid stochastic experts
Proceedings of the 40th International Conference on Machine Learning (ICML). PMLR 202:34809-34830, 2023.
L. Zierahn, D. van der Hoeven, N. Cesa-Bianchi, and G. Neu
Nonstochastic contextual combinatorial bandits
Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR 206:8771-8813, 2023.
C. Rouyer, D. van der Hoeven, N. Cesa-Bianchi, and Y. Seldin
A near-optimal best-of-both-worlds algorithm for online learning with feedback graphs
Advances in Neural Information Processing Systems 35 (NeurIPS), 2022.
E. Esposito, F. Fusco, D. van der Hoeven, N. Cesa-Bianchi
Learning on the edge: Online learning with stochastic feedback graphs
Advances in Neural Information Processing Systems 35 (NeurIPS), 2022.
N. Cesa-Bianchi, T. Cesari, R. Colomboni, C. Gentile, and Y. Mansour
Nonstochastic bandits with composite anonymous feedback
Journal of Machine Learning Research. JMLR, 23(227):1-24, 2022.
D. van der Hoeven and N. Cesa-Bianchi
Nonstochastic bandits and experts with arm-dependent delays
Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR 151:2022-2044, 2022.
P. Laforgue, G. Clerici, N. Cesa-Bianchi, and Ran Gilad-Bachrach
A last switch dependent analysis of satiation and seasonality in bandits
Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR 151:971-990, 2022.
N. Cesa-Bianchi, T. Cesari, Y. Mansour, and V. Perchet
ROI maximization in stochastic online decision-making
Advances in Neural Information Processing Systems 34 (NeurIPS), 2021.
D. van der Hoeven, F. Fusco, and N. Cesa-Bianchi
Beyond bandit feedback in online multiclass classification
Advances in Neural Information Processing Systems 34 (NeurIPS), 2021.
C. Rouyer, Y. Seldin, and N. Cesa-Bianchi
An algorithm for stochastic and adversarial bandits with switching costs
Proceedings of the 38th International Conference on Machine Learning (ICML). PMLR 139:9127-9135, 2021.
L. Cella and N. Cesa-Bianchi
Stochastic bandits with delay-dependent payoffs
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR, 108:1168-1177, 2020.
T. Thune, N. Cesa-Bianchi, and Y. Seldin
Nonstochastic multiarmed bandits with unrestricted delays
Advances in Neural Information Processing Systems 32 (NeurIPS), 2019.
I. Kuzborskij, L. Cella, and N. Cesa-Bianchi
Efficient linear bandits through matrix sketching
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR, 89:177-185, 2019.
N. Cesa-Bianchi and O. Shamir
Bandit regret scaling with the effective loss range (revised version)
Proceedings of the 29th International Conference on Algorithmic Learning Theory (ALT). PMLR 83:128-151, 2018.
N. Cesa-Bianchi, C. Gentile, G. Lugosi, G. Neu
Boltzmann exploration done right
Advances in Neural Information Processing Systems 30 (NIPS). Pages 6284-6293, 2017.
N. Alon, N. Cesa-Bianchi, C. Gentile, S. Mannor, Y. Mansour, and O. Shamir
Nonstochastic multi-armed bandits with graph-structured feedback
SIAM Journal on Computing. 46(6):1785-1826, 2017.
N. Cesa-Bianchi, P. Gaillard, C. Gentile, and S. Gerchinovitz
Algorithmic chaining and the role of partial feedback in online nonparametric learning
Proceedings of the 30th Conference on Learning Theory (COLT). PMLR 65:465-481, 2017.
N. Cesa-Bianchi
Multi-armed bandit problem
Encyclopedia of Algorithms. Pages 1356-1359, 2016.
N. Alon, N. Cesa-Bianchi, O. Dekel, and T. Koren
Online learning with feedback graphs: beyond bandits
Proceedings of the 28th Conference on Learning Theory (COLT). JMLR Workshop and Conference Proceedings, 40:23-35, 2015.
N. Cesa-Bianchi, C. Gentile, and G. Zappella
A gang of bandits
Advances in Neural Information Processing Systems 26 (NIPS). Pages 737-745, 2013.
S. Bubeck, N. Cesa-Bianchi, and G. Lugosi
Bandits with heavy tail
IEEE Transactions on Information Theory, 59(11):7711-7717, 2013.
S. Bubeck and N. Cesa-Bianchi
Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Foundations and Trends in Machine Learning, 5(1)1-122, 2012.
S. Bubeck, N. Cesa-Bianchi, and S. Kakade
Towards minimax policies for online linear optimization with bandit feedback
Proceedings of the 25th Annual Conference on Learning Theory (COLT). JMLR Workshop and Conference Proceedings, 23:41.1-41.14, 2012.
N. Cesa-Bianchi and G. Lugosi
Combinatorial bandits
Journal of Computer and Systems Sciences, 78:1404-1422, 2012.
P. Auer, N. Cesa-Bianchi, and P. Fischer
Finite-time analysis of the multiarmed bandit problem
Machine Learning, 47(2/3):235-256, 2002.
P. Auer, N. Cesa-Bianchi, Y. Freund, and R.E. Schapire
The nonstochastic multiarmed bandit problem
SIAM Journal on Computing, 32(1):48-77, 2002.

Learning on Graphs

G. Le Falher, N. Cesa-Bianchi, C. Gentile, F. Vitale
On the troll-trust model for edge sign prediction in social networks
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS). JMLR Workshop and Conference Proceedings, 54:402-411, 2017.
N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella
A linear time active learning algorithm for link classification
Advances in Neural Information Processing Systems 25 (NIPS). Pages 1619-1627, 2012.
N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella
A correlation clustering approach to link classification in signed networks
Proceedings of the 25th Annual Conference on Learning Theory (COLT). JMLR Workshop and Conference Proceedings, 23:34.1-34.20, 2012.
F. Vitale, N. Cesa-Bianchi, C. Gentile, and G. Zappella
See the tree through the lines: the Shazoo algorithm
Advances in Neural Information Processing Systems 24 (NIPS). Pages 1584-1592, 2011.
Full paper.
N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella
Active learning on trees and graphs
Proceedings of the 23rd Conference on Learning Theory (COLT). Omnipress, 2010.
N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella
Random spanning trees and the prediction of weighted graphs
Journal of Machine Learning Research, 14:1251-1284, 2013.
N. Cesa-Bianchi, C. Gentile, and F. Vitale
Predicting the labels of an unknown graph via adaptive exploration
Theoretical Computer Science, 412(19):1791-1804, 2011.
N. Cesa-Bianchi, C. Gentile, and F. Vitale
Fast and optimal prediction on a labeled tree
Proceedings of the 22nd Conference on Learning Theory (COLT). Omnipress, 2009.

Online Learning

D. van der Hoeven, N. Zhivotovskiy, and N. Cesa-Bianchi
A regret-variance trade-off in online learning
Advances in Neural Information Processing Systems 35 (NeurIPS), 2022.
N. Cesa-Bianchi and F. Orabona
Online learning algorithms
Annual Review of Statistics and Its Application, 8:165-190, 2021.
I. Kuzborskij and N. Cesa-Bianchi
Locally-adaptive nonparametric online learning
Advances in Neural Information Processing Systems 33 (NeurIPS), 2020.
I. Kuzborskij and N. Cesa-Bianchi
Nonparametric online regression while learning the metric
Advances in Neural Information Processing Systems 30 (NIPS). Pages 667-676, 2017.
R. De Rosa and N. Cesa-Bianchi
Confidence decision trees via online and active learning for streaming data
Journal of Artificial Intelligence Research, 60:1031-1055, 2017.
R. De Rosa, I. Gori, F. Cuzzolin, and N. Cesa-Bianchi
Active incremental recognition of human activities in a streaming context
Pattern Recognition Letters. 99:48-56, 2017.
H. Luo, A. Agarwal, N. Cesa-Bianchi, and J. Langford
Efficient second order online learning by sketching
Advances in Neural Information Processing Systems 29 (NIPS). Pages 902-910, 2016.
R. De Rosa, F. Orabona, and N. Cesa-Bianchi
The ABACOC algorithm: A novel approach for nonparametric classification of data streams
Proceedings of the IEEE International Conference on Data Mining (ICDM). Pages 733-738, 2015.
Long version.
F. Orabona, K. Crammer, and N. Cesa-Bianchi
A generalized online mirror descent with applications to classification and regression
Machine Learning, 99(3):411-435, 2015.
N. Cesa-Bianchi and O. Shamir
Efficient transductive online learning via randomized rounding
In: Empirical Inference, Festschrift in Honor of Vladimir N. Vapnik. Springer, 2013.
(A preliminary version Efficient online learning via randomized rounding appeared in: Advances in Neural Information Processing Systems 24 (NIPS 2011). Pages 343-351.)
F. Orabona, N. Cesa-Bianchi, and C. Gentile
Beyond logarithmic bounds in online learning
Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS). JMLR Workshop and Conference Proceedings, 22:823-831, 2012.
F. Orabona and N. Cesa-Bianchi
Better algorithms for selective sampling
Proceedings of the 28th International Conference on Machine Learning (ICML). Omnipress, 2011.
N. Cesa-Bianchi, S. Shalev-Shwartz, and O. Shamir
Quantity makes quality: learning with partial views
Proceedings of the 25th AAAI Conference on Artificial Intelligence (Nectar Program). AAAI Press, 2011.
N. Cesa-Bianchi, S. Shalev-Shwartz, and O. Shamir
Online learning of noisy data
IEEE Transaction on Information Theory, 57(12):7907-7931, 2011.
L. Jie, F. Orabona, M. Fornoni, B. Caputo, and N. Cesa-Bianchi
OM-2: An online multi-class multi-kernel learning algorithm
Proceedings of the 4th IEEE Online Learning for Computer Vision Workshop. IEEE Press, 2010.
N. Cesa-Bianchi, S. Shalev-Shwartz, and O. Shamir
Efficient learning with partially observed attributes
Journal of Machine Learning Research, 12:2857-2878, 2011.
G. Cavallanti, N. Cesa-Bianchi, and C. Gentile
Linear algorithms for online multitask classification
Journal of Machine Learning Research, 11:2901-2934, 2010.
N. Cesa-Bianchi, C. Gentile, and F. Orabona
Robust bounds for classification via selective sampling
Proceedings of the 26th International Conference on Machine Learning (ICML). Omnipress, 2009.
G. Cavallanti, N. Cesa-Bianchi, and C. Gentile
Tracking the best hyperplane with a simple budget Perceptron
Machine Learning, 69(2/3):143-167. Springer, 2007.
N. Cesa-Bianchi
Applications of regularized least squares to pattern classification
Theoretical Computer Science, 382(3):221-231. Elsevier, 2007.
N. Cesa-Bianchi, C. Gentile, and L. Zaniboni
Worst-case analysis of selective sampling for linear classification
Journal of Machine Learning Research, 7:1205-1230, 2006.
N. Cesa-Bianchi, C. Gentile, and L. Zaniboni
Hierarchical classification: combining Bayes with SVM
Proceedings of the 23rd International Conference on Machine Learning (ICML), 2006.
N. Cesa-Bianchi, C. Gentile, and L. Zaniboni
Incremental algorithms for hierarchical classification
Journal of Machine Learning Research, 7:31--54, 2006.
N. Cesa-Bianchi, A. Conconi, and C. Gentile
A second-order Perceptron algorithm
SIAM Journal on Computing, 34(3):640-668. SIAM, 2005.
P. Auer, N. Cesa-Bianchi, and C. Gentile
Adaptive and self-confident on-line learning algorithms
Journal of Computer and System Sciences, 64(1):48-75, 2002.
N. Cesa-Bianchi
Analysis of two gradient-based algorithms for on-line regression
Journal of Computer and System Sciences, 59(3):392-411, 1999.
P. Auer and N. Cesa-Bianchi
On-line learning with malicious noise and the closure algorithm
Annals of AI and Mathematics, 23(1/2):83-99, 1998.
N. Cesa-Bianchi, P.M. Long, and M.K. Warmuth
Worst-case quadratic loss bounds for prediction using linear functions and gradient descent
IEEE Transactions on Neural Networks, 7(3):604-619, 1996.
A. Bertoni, N. Cesa-Bianchi e G. Fiorino
Efficient learning with equivalence queries of conjunctions of modulo functions
Information Processing Letters, 56:15--17, 1995.

Statistical Learning Theory

M. Bressan, N. Cesa-Bianchi, E. Esposito, Y. Mansour, S. Moran, and M. Thiessen.
A theory of interpretable approximations
Proceedings of the 37th Annual Conference on Learning Theory (COLT). PMLR 247:648-668, 2024.
I. Kuzborskij, N. Cesa-Bianchi, and C. Szepesvari
Distribution-Dependent Analysis of Gibbs-ERM Principle
Proceedings of the 32nd Annual Conference on Learning Theory (COLT). PMLR 99:2028-2054, 2019.
N. Cesa-Bianchi, Y. Mansour, and O. Shamir
On the complexity of learning with kernels
Proceedings of the 28th Annual Conference on Learning Theory (COLT). JMLR Workshop and Conference Proceedings, 40:297-325, 2015.
G. Cavallanti, N. Cesa-Bianchi, and C. Gentile
Learning noisy linear classifiers via adaptive and selective sampling
Machine Learning, 83:71-102, 2011.
N. Cesa-Bianchi and C. Gentile
Improved risk tail bounds for on-line algorithms
IEEE Transactions on Information Theory, 54(1):386-390, 2008.
N. Cesa-Bianchi, A. Conconi, and C. Gentile
On the generalization ability of on-line learning algorithms
IEEE Transactions on Information Theory, 50(9):2050-2057, 2004.
N. Cesa-Bianchi, E. Dichterman, P. Fischer, E. Shamir, and H.U. Simon
Sample-efficient strategies for learning in the presence of noise
Journal of the ACM, 46(5):684-719, 1999.
N. Alon, S. Ben-David, N. Cesa-Bianchi, and D. Haussler
Scale-sensitive dimensions, uniform convergence, and learnability
Journal of the ACM, 44(4):615-631, 1997.
S. Ben-David, N. Cesa-Bianchi, D. Haussler, and P.M. Long
Characterizations of learnability for classes of {0,..,n}-valued functions
Journal of Computer and System Sciences, 50(1):74-86, 1995.

Prediction with Expert Advice and Game-Theoretic Learning

N. Cesa-Bianchi, O. Dekel, O Shamir
Online learning with switching costs and other adaptive adversaries
Advances in Neural Information Processing Systems 26. Pages 1160-1168, 2013.
E. Gofer, N. Cesa-Bianchi, C. Gentile, and Y. Mansour
Regret minimization for branching experts
Proceedings of the 26th Conference on Learning Theory. JMLR Workshop and Conference Proceedings, 30:618-638, 2013.
N. Cesa-Bianchi, P. Gaillard, G. Lugosi, and G. Stoltz
Mirror Descent meets Fixed Share (and feels no regret)
Advances in Neural Information Processing Systems 25. Pages 989-997, 2012.
N. Cesa-Bianchi, Y. Mansour, and G. Stoltz
Improved second-order bounds for prediction with expert advice
Machine Learning, 66(2/3):321-352, 2007.
N. Cesa-Bianchi, G. Lugosi, and G. Stoltz
Regret minimization under partial monitoring
Mathematics of Operations Research, 31(3):562-580, 2006.
N. Cesa-Bianchi, G. Lugosi, and G. Stoltz
Minimizing regret with label efficient prediction
IEEE Transactions on Information Theory, 51(6):2152-2162, 2005.
N. Cesa-Bianchi and G. Lugosi
Potential-based algorithms in on-line prediction and game theory
Machine Learning, 51(3):239-261, 2003.
N. Cesa-Bianchi
Universal prediction
In: Principles of Nonparametric Learning
Springer (CISM courses and lectures no. 434), 2002.
N. Cesa-Bianchi and G. Lugosi
Worst-case bounds for the logarithmic loss of predictors
Machine Learning, 43(3):247-264, 2001.
N. Cesa-Bianchi and G. Lugosi
On prediction of individual sequences
Annals of Statistics, 27(6):1865-1895, 1999.
N. Cesa-Bianchi, D.P. Helmbold, and S. Panizza
On Bayes methods for on-line boolean prediction
Algorithmica, 22(1/2):112-137, 1998.
N. Cesa-Bianchi, Y. Freund, D.P. Helmbold, D. Haussler, R. Schapire, and M.K. Warmuth
How to use expert advice
Journal of the ACM, 44(3):427-485, 1997.
N. Cesa-Bianchi, Y. Freund, D.P. Helmbold, and M.K. Warmuth
On-line prediction and conversion strategies
Machine Learning, 25:71-110, 1996.

Bioinformatics

M. Frasca and N. Cesa-Bianchi
Multitask protein function prediction through task dissimilarity
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16:1550-1560, 2019.
N. Cesa-Bianchi, M. Re, and G. Valentini
Synergy of multilabel hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference
Machine Learning, 88:209-241, 2012.
N. Cesa-Bianchi and G. Valentini
Hierarchical cost-sensitive algorithms for genome-wide gene function prediction
Proceedings of the 3rd International Workshop on Machine Learning in Systems Biology, JMLR Workshop and Conference Proceedings, 8:14-29, 2010.
G. Valentini and N. Cesa-Bianchi
HCGene: a software tool to support the hierarchical classification of genes
Bioinformatics, 24(5):729-731, 2008.

Other Areas

M. Bressan, N. Cesa-Bianchi, E. Esposito, Y. Mansour, S. Moran, and M. Thiessen.
A theory of interpretable approximations.
Proceedings of the 37th Conference on Learning Theory (COLT), PMLR 247:648-668, 2024.
Y. Seldin, F. Laviolette, N. Cesa-Bianchi, J. Shawe-Taylor, and P. Auer
PAC-Bayesian Inequalities for Martingales
IEEE Transactions on Information Theory, 58(12):7086-7093, 2012.
P. Auer and N. Cesa-Bianchi
A distributed voting scheme to maximize preferences
RAIRO - Theoretical Informatics and Applications, 40:389-403, 2006.
N. Cesa-Bianchi and G. Lugosi
Minimax values and metric entropy bounds for portfolio selection problems
Communicated at the First World Congress of the Game Theory Society (Games 2000).
N. Cesa-Bianchi and D. Haussler,
A graph-theoretic generalization of the Sauer-Shelah lemma
Discrete Applied Mathematics, 86(1):27-35, 1998.
N. Cesa-Bianchi, A. Krogh and M.K. Warmuth
Bounds on approximate steepest descent for likelihood maximization in exponential families
IEEE Transactions on Information Theory, 40(4):1215-1218, 1994.
B. Apolloni, N. Cesa-Bianchi, and D. De Falco
A numerical implementation of quantum annealing
Stochastic Processes, Physics and Geometry: Proceedings of the Ascona-Locarno Conference, pages 97-111, 1988.
G. Cattaneo and N. Cesa-Bianchi
Microcanonical annealing on neural networks
Proceedings of the First Annual Meeting of the International Neural Network Society, page 81, 1988.