Prediction with Expert Advice and Game-Theoretic Learning

• N. Cesa-Bianchi, C. Gentile, and F. Vitale
  Learning unknown graphs
  The 20th International Conference on Algorithmic Learning Theory. Springer, 2009.

• 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.

• 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.

• G. Cavallanti, N. Cesa-Bianchi, and C. Gentile
  Linear algorithms for online multitask and multiview classification
  Journal submission, 2009.

• 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.

• N. Cesa-Bianchi, A. Conconi, and C. Gentile
  Margin-based algorithms for information filtering
  Advances in Neural Information Processing Systems 15, pages 470-477. MIT Press, 2003.

• 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.

• G. Cavallanti, N. Cesa-Bianchi, and C. Gentile
  Linear Classification and Selective Sampling Under Low Noise Conditions
  Advances in Neural Information Processing Systems 22, 2009.

• 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.

• 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.

• N. Cesa-Bianchi and G. Lugosi
  Combinatorial bandits
  Submitted for journal publication, 2010.

• 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.

• 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, 2009.

• G. Valentini and N. Cesa-Bianchi
  HCGene: a software tool to support the hierarchical classification of genes
  Bioinformatics, 24(5):729-731, 2008.

• 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.