Nicolò Cesa-Bianchi - Selected papers

nicolò cesa-bianchi - selected papers

"This isn't class warfare. This is Math." - B. Obama

Prediction with Expert Advice and Game-Theoretic Learning

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.
Slides presented at the IEEE 2006 Information Theory Workshop.
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: L. Györfi (editor), 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.

Bandit Problems

Y. Seldin, N. Cesa-Bianchi, P. Auer, F. Laviolette, and J. Shawe-Taylor
PAC-Bayes-Bernstein inequality for martingales and its application to multiarmed bandits
JMLR Workshop and Conference Proceedings, 2011.
N. Cesa-Bianchi and G. Lugosi
Combinatorial bandits
Journal of Computer and Systems Sciences. To appear.
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

F. Vitale, N. Cesa-Bianchi, C. Gentile, and G. Zappella
See the tree through the lines: the Shazoo algorithm
Proceedings of the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011). Curran Associates, 2012.
N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella
Active learning on trees and graphs
Proceedings of the 23rd Annual Conference on Learning Theory. Omnipress, 2010.
N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella
Random spanning trees and the prediction of weighted graphs
Proceedings of the 27th International Conference on Machine Learning. Omnipress, 2010.
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 Annual Conference on Learning Theory. Omnipress, 2009.

Pattern Classification and Regression

F. Orabona, N. Cesa-Bianchi, and C. Gentile
Beyond logarithmic bounds in online learning
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012).
N. Cesa-Bianchi and O. Shamir
Efficient online learning via randomized rounding
Proceedings of the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011). Curran Associates, 2012.
F. Orabona and N. Cesa-Bianchi
Better algorithms for selective sampling
Proceedings of the 28th International Conference on Machine Learning. 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 with kernels
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
4th IEEE Online Learning for Computer Vision Workshop, 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, 11:2597-2630, 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. 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 classification problems
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, 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.
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.

Statistical Learning Theory

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.

Boolean Learning and Learning with Queries

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.
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.

Bioinformatics

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. To appear.
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

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.