Nicolò Cesa-Bianchi

According to our database1, Nicolò Cesa-Bianchi authored at least 133 papers between 1988 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

Legend:

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PhD thesis 
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Bibliography

2020
Locally-Adaptive Nonparametric Online Learning.
CoRR, 2020

2019
Multitask Protein Function Prediction through Task Dissimilarity.
IEEE/ACM Trans. Comput. Biology Bioinform., 2019

Delay and Cooperation in Nonstochastic Bandits.
J. Mach. Learn. Res., 2019

Stochastic Bandits with Delay-Dependent Payoffs.
CoRR, 2019

Repeated A/B Testing.
CoRR, 2019

Cooperative Online Learning: Keeping your Neighbors Updated.
CoRR, 2019

Nonstochastic Multiarmed Bandits with Unrestricted Delays.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Correlation Clustering with Adaptive Similarity Queries.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Distribution-Dependent Analysis of Gibbs-ERM Principle.
Proceedings of the Conference on Learning Theory, 2019

Dynamic Pricing with Finitely Many Unknown Valuations.
Proceedings of the Algorithmic Learning Theory, 2019

Efficient Linear Bandits through Matrix Sketching.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction.
CoRR, 2018

Nonstochastic Bandits with Composite Anonymous Feedback.
Proceedings of the Conference On Learning Theory, 2018

Bandit Regret Scaling with the Effective Loss Range.
Proceedings of the Algorithmic Learning Theory, 2018

2017
Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback.
SIAM J. Comput., 2017

Active Incremental Recognition of Human Activities in a Streaming Context.
Pattern Recognition Letters, 2017

Confidence Decision Trees via Online and Active Learning for Streaming Data.
J. Artif. Intell. Res., 2017

Online Nonparametric Learning, Chaining, and the Role of Partial Feedback.
CoRR, 2017

Nonparametric Online Regression while Learning the Metric.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Boltzmann Exploration Done Right.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning.
Proceedings of the 30th Conference on Learning Theory, 2017

On the Troll-Trust Model for Edge Sign Prediction in Social Networks.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Multi-armed Bandit Problem.
Encyclopedia of Algorithms, 2016

Active Learning for Online Recognition of Human Activities from Streaming Videos.
CoRR, 2016

Efficient Second Order Online Learning via Sketching.
CoRR, 2016

Efficient Second Order Online Learning by Sketching.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Delay and Cooperation in Nonstochastic Bandits.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Regret Minimization for Reserve Prices in Second-Price Auctions.
IEEE Trans. Information Theory, 2015

A generalized online mirror descent with applications to classification and regression.
Machine Learning, 2015

Splitting with confidence in decision trees with application to stream mining.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

The ABACOC Algorithm: A Novel Approach for Nonparametric Classification of Data Streams.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

On the Complexity of Learning with Kernels.
Proceedings of The 28th Conference on Learning Theory, 2015

Online Learning with Feedback Graphs: Beyond Bandits.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Online Action Recognition via Nonparametric Incremental Learning.
Proceedings of the British Machine Vision Conference, 2014

2013
Bandits With Heavy Tail.
IEEE Trans. Information Theory, 2013

Random spanning trees and the prediction ofweighted graphs.
J. Mach. Learn. Res., 2013

A Gang of Bandits.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Online Learning with Switching Costs and Other Adaptive Adversaries.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

From Bandits to Experts: A Tale of Domination and Independence.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Regret Minimization for Branching Experts.
Proceedings of the COLT 2013, 2013

Efficient Transductive Online Learning via Randomized Rounding.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
PAC-Bayesian Inequalities for Martingales.
IEEE Trans. Information Theory, 2012

Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference.
Machine Learning, 2012

PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Beyond Logarithmic Bounds in Online Learning.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

A Correlation Clustering Approach to Link Classification in Signed Networks.
Proceedings of the COLT 2012, 2012

Towards Minimax Policies for Online Linear Optimization with Bandit Feedback.
Proceedings of the COLT 2012, 2012

Combinatorial bandits.
J. Comput. Syst. Sci., 2012

Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems.
Foundations and Trends in Machine Learning, 2012

Memory Constraint Online Multitask Classification
CoRR, 2012

A new look at shifting regret
CoRR, 2012

A Linear Time Active Learning Algorithm for Link Classification.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Mirror Descent Meets Fixed Share (and feels no regret).
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Online Learning of Noisy Data.
IEEE Trans. Information Theory, 2011

Predicting the labels of an unknown graph via adaptive exploration.
Theor. Comput. Sci., 2011

Learning noisy linear classifiers via adaptive and selective sampling.
Machine Learning, 2011

Efficient Learning with Partially Observed Attributes.
J. Mach. Learn. Res., 2011

PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off
CoRR, 2011

See the Tree Through the Lines: The Shazoo Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Efficient Online Learning via Randomized Rounding.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Ensembles and Multiple Classifiers: A Game-Theoretic View.
Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

Better Algorithms for Selective Sampling.
Proceedings of the 28th International Conference on Machine Learning, 2011

The Game-Theoretic Approach to Machine Learning and Adaptation.
Proceedings of the Adaptive and Intelligent Systems - Second International Conference, 2011

Quantity Makes Quality: Learning with Partial Views.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Guest Editorial: Learning from multiple sources.
Machine Learning, 2010

Hierarchical Cost-Sensitive Algorithms for Genome-Wide Gene Function Prediction.
Proceedings of the third International Workshop on Machine Learning in Systems Biology, 2010

Linear Algorithms for Online Multitask Classification.
J. Mach. Learn. Res., 2010

Random Spanning Trees and the Prediction of Weighted Graphs.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

OM-2: An online multi-class Multi-Kernel Learning algorithm Luo Jie.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010

Online Learning of Noisy Data with Kernels.
Proceedings of the COLT 2010, 2010

Active Learning on Trees and Graphs.
Proceedings of the COLT 2010, 2010

2009
Robust bounds for classification via selective sampling.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Fast and Optimal Prediction on a Labeled Tree.
Proceedings of the COLT 2009, 2009

Online discriminative learning: theory and applications.
Proceedings of the 2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009

Learning Unknown Graphs.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008
Improved Risk Tail Bounds for On-Line Algorithms.
IEEE Trans. Information Theory, 2008

HCGene: a software tool to support the hierarchical classification of genes.
Bioinformatics, 2008

Linear Classification and Selective Sampling Under Low Noise Conditions.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Applications of regularized least squares to pattern classification.
Theor. Comput. Sci., 2007

Improved second-order bounds for prediction with expert advice.
Machine Learning, 2007

Tracking the best hyperplane with a simple budget Perceptron.
Machine Learning, 2007

2006
Foreword.
Theor. Comput. Sci., 2006

Regret Minimization Under Partial Monitoring.
Math. Oper. Res., 2006

Worst-Case Analysis of Selective Sampling for Linear Classification.
J. Mach. Learn. Res., 2006

Incremental Algorithms for Hierarchical Classification.
J. Mach. Learn. Res., 2006

A distributed voting scheme to maximize preferences.
ITA, 2006

Hierarchical classification: combining Bayes with SVM.
Proceedings of the Machine Learning, 2006

Tracking the Best Hyperplane with a Simple Budget Perceptron.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

Prediction, learning, and games.
Cambridge University Press, ISBN: 978-0-511-54692-1, 2006

2005
Minimizing regret with label efficient prediction.
IEEE Trans. Information Theory, 2005

A Second-Order Perceptron Algorithm.
SIAM J. Comput., 2005

A Distributed Architecture for Management and Retrieval of Extended Points of Interest.
Proceedings of the 25th International Conference on Distributed Computing Systems Workshops (ICDCS 2005 Workshops), 2005

2004
On the Generalization Ability of On-Line Learning Algorithms.
IEEE Trans. Information Theory, 2004

Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Incremental Algorithms for Hierarchical Classification.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Towards Highly Adaptive Services for Mobile Computing.
Proceedings of the Mobile Information Systems, 2004

Regret Bounds for Hierarchical Classification with Linear-Threshold Functions.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

Applications of Regularized Least Squares to Classification Problems.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003
Potential-Based Algorithms in On-Line Prediction and Game Theory.
Machine Learning, 2003

Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
The Nonstochastic Multiarmed Bandit Problem.
SIAM J. Comput., 2002

Finite-time Analysis of the Multiarmed Bandit Problem.
Machine Learning, 2002

Adaptive and Self-Confident On-Line Learning Algorithms.
J. Comput. Syst. Sci., 2002

Kernel Methods for Document Filtering.
Proceedings of The Eleventh Text REtrieval Conference, 2002

Margin-Based Algorithms for Information Filtering.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Editors' Introduction.
Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2001
Worst-Case Bounds for the Logarithmic Loss of Predictors.
Machine Learning, 2001

Potential-Based Algorithms in Online Prediction and Game Theory.
Proceedings of the Computational Learning Theory, 2001

2000
Gambling in a rigged casino: The adversarial multi-armed bandit problem
Electronic Colloquium on Computational Complexity (ECCC), 2000

1999
Guest Editors' Introduction.
Machine Learning, 1999

Analysis of Two Gradient-Based Algorithms for On-Line Regression.
J. Comput. Syst. Sci., 1999

Sample-Efficient Strategies for Learning in the Presence of Noise.
J. ACM, 1999

Minimax Regret Under log Loss for General Classes of Experts.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
A Graph-theoretic Generalization of the Sauer-Shelah Lemma.
Discrete Applied Mathematics, 1998

On-Line Learning with Malicious Noise and the Closure Algorithm.
Ann. Math. Artif. Intell., 1998

On Bayes Methods for On-Line Boolean Prediction.
Algorithmica, 1998

Finite-Time Regret Bounds for the Multiarmed Bandit Problem.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

On Sequential Prediction of Individual Sequences Relative to a Set of Experts.
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997
How to use expert advice.
J. ACM, 1997

Scale-sensitive dimensions, uniform convergence, and learnability.
J. ACM, 1997

Randomized Hypotheses and Minimum Disagreement Hypotheses for Learning with Noise.
Proceedings of the Computational Learning Theory, Third European Conference, 1997

1996
Worst-case quadratic loss bounds for prediction using linear functions and gradient descent.
IEEE Trans. Neural Networks, 1996

On-line Prediction and Conversion Strategies.
Machine Learning, 1996

Noise-Tolerant Learning Near the Information-Theoretic Bound.
Proceedings of the Twenty-Eighth Annual ACM Symposium on the Theory of Computing, 1996

Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract).
Proceedings of the Fifteenth Annual ACM Symposium on Principles of Distributed Computing, 1996

1995
Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions.
J. Comput. Syst. Sci., 1995

Efficient Learning with Equivalence Queries of Conjunctions of Modulo Functions.
Inf. Process. Lett., 1995

Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem.
Proceedings of the 36th Annual Symposium on Foundations of Computer Science, 1995

1994
Bounds on approximate steepest descent for likelihood maximization in exponential families.
IEEE Trans. Information Theory, 1994

1993
Worst-Case Quadratic Loss Bounds for a Generalization of the Widrow-Hoff Rule.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992
Characterizations of Learnability for Classes of {O, ..., n}-Valued Functions.
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1990
Learning the Distribution in the Extended PAC Model.
Proceedings of the Algorithmic Learning Theory, First International Workshop, 1990

1988
Microcanonical annealing on neural networks.
Neural Networks, 1988


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