Corinna Cortes

According to our database1, Corinna Cortes authored at least 102 papers between 1993 and 2024.

Collaborative distances:

Awards

ACM Fellow

ACM Fellow 2022, "For theoretical and practical contributions to machine learning, industrial leadership, and service to the field".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Theory and algorithms for learning with rejection in binary classification.
Ann. Math. Artif. Intell., April, 2024

Best-effort adaptation.
Ann. Math. Artif. Intell., April, 2024

Cardinality-Aware Set Prediction and Top-k Classification.
CoRR, 2024

A Theory of Learning with Competing Objectives and User Feedback.
Proceedings of the Artificial Intelligence and Image Analysis, 2024

Differentially Private Domain Adaptation with Theoretical Guarantees.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Theory and Algorithm for Batch Distribution Drift Problems.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021
Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment.
CoRR, 2021

Boosting with Multiple Sources.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Discriminative Technique for Multiple-Source Adaptation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Relative Deviation Margin Bounds.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Multiple-Source Adaptation with Domain Classifiers.
CoRR, 2020

Beyond Individual and Group Fairness.
CoRR, 2020

Agnostic Learning with Multiple Objectives.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Learning with Dependent Stochastic Feedback Graphs.
Proceedings of the 37th International Conference on Machine Learning, 2020

Adaptive Region-Based Active Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Understanding the Effects of Batching in Online Active Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Adaptation Based on Generalized Discrepancy.
J. Mach. Learn. Res., 2019

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles.
CoRR, 2019

Relative deviation learning bounds and generalization with unbounded loss functions.
Ann. Math. Artif. Intell., 2019

Regularized Gradient Boosting.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning GANs and Ensembles Using Discrepancy.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Active Learning with Disagreement Graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Online Learning with Sleeping Experts and Feedback Graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Online Non-Additive Path Learning under Full and Partial Information.
Proceedings of the Algorithmic Learning Theory, 2019

Region-Based Active Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Learning with Abstention.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
On-line Learning with Abstention.
CoRR, 2017

AdaNet: Adaptive Structural Learning of Artificial Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Structured Prediction Theory and Voted Risk Minimization.
CoRR, 2016

Structured Prediction Theory Based on Factor Graph Complexity.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Boosting with Abstention.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning with Rejection.
Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

Hancock: A Language for Analyzing Transactional Data Streams.
Proceedings of the Data Stream Management - Processing High-Speed Data Streams, 2016

2015
Voted Kernel Regularization.
CoRR, 2015

Kernel Extraction via Voted Risk Minimization.
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

Adaptation Algorithm and Theory Based on Generalized Discrepancy.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Structural Maxent Models.
Proceedings of the 32nd International Conference on Machine Learning, 2015

On-Line Learning Algorithms for Path Experts with Non-Additive Losses.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Domain adaptation and sample bias correction theory and algorithm for regression.
Theor. Comput. Sci., 2014

Deep Boosting.
Proceedings of the 31th International Conference on Machine Learning, 2014

Ensemble Methods for Structured Prediction.
Proceedings of the 31th International Conference on Machine Learning, 2014

Learning Ensembles of Structured Prediction Rules.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

2013
Learning Kernels Using Local Rademacher Complexity.
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

Multi-Class Classification with Maximum Margin Multiple Kernel.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Algorithms for Learning Kernels Based on Centered Alignment.
J. Mach. Learn. Res., 2012

Accuracy at the Top.
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
A Dual Coordinate Descent Algorithm for SVMs Combined with Rational Kernels.
Int. J. Found. Comput. Sci., 2011

Ensembles of Kernel Predictors.
Proceedings of the UAI 2011, 2011

Domain Adaptation in Regression.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

2010
On the Impact of Kernel Approximation on Learning Accuracy.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Half Transductive Ranking.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Large-Scale Training of SVMs with Automata Kernels.
Proceedings of the Implementation and Application of Automata, 2010

Learning Bounds for Importance Weighting.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Generalization Bounds for Learning Kernels.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Two-Stage Learning Kernel Algorithms.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
New Generalization Bounds for Learning Kernels
CoRR, 2009

Stability Analysis and Learning Bounds for Transductive Regression Algorithms
CoRR, 2009

L2 Regularization for Learning Kernels.
Proceedings of the UAI 2009, 2009

Learning Non-Linear Combinations of Kernels.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Polynomial Semantic Indexing.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Invited talk: Can learning kernels help performance?
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Kernel methods for learning languages.
Theor. Comput. Sci., 2008

On the Computation of the Relative Entropy of Probabilistic Automata.
Int. J. Found. Comput. Sci., 2008

Stability of transductive regression algorithms.
Proceedings of the Machine Learning, 2008

Learning with Weighted Transducers.
Proceedings of the Finite-State Methods and Natural Language Processing, 2008

Sample Selection Bias Correction Theory.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007
L<sub>P</sub> Distance and Equivalence of Probabilistic Automata.
Int. J. Found. Comput. Sci., 2007

An Alternative Ranking Problem for Search Engines.
Proceedings of the Experimental Algorithms, 6th International Workshop, 2007

Magnitude-preserving ranking algorithms.
Proceedings of the Machine Learning, 2007

Learning Languages with Rational Kernels.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
On the Computation of Some Standard Distances Between Probabilistic Automata.
Proceedings of the Implementation and Application of Automata, 2006

On Transductive Regression.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Efficient Computation of the Relative Entropy of Probabilistic Automata.
Proceedings of the LATIN 2006: Theoretical Informatics, 2006

Learning Linearly Separable Languages.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005
Moment Kernels for Regular Distributions.
Mach. Learn., 2005

A general regression technique for learning transductions.
Proceedings of the Machine Learning, 2005

Margin-Based Ranking Meets Boosting in the Middle.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004
Hancock: A language for analyzing transactional data streams.
ACM Trans. Program. Lang. Syst., 2004

Rational Kernels: Theory and Algorithms.
J. Mach. Learn. Res., 2004

Confidence Intervals for the Area Under the ROC Curve.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Distribution kernels based on moments of counts.
Proceedings of the Machine Learning, 2004

2003
AUC Optimization vs. Error Rate Minimization.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Weighted automata kernels - general framework and algorithms.
Proceedings of the 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003, 2003

Lattice kernels for spoken-dialog classification.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Positive Definite Rational Kernels.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Communities of interest.
Intell. Data Anal., 2002

Rational Kernels.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
Signature-Based Methods for Data Streams.
Data Min. Knowl. Discov., 2001

2000
Context-Free Recognition with Weighted Automata.
Grammars, 2000

Hancock: a language for extracting signatures from data streams.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1999
Squashing Flat Files Flatter.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

Information Mining Platforms: An Infrastructure for KDD Rapid Deployment.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

1998
Giga-Mining.
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

1995
Support-Vector Networks.
Mach. Learn., 1995

Boosting Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

1994
Boosting and Other Ensemble Methods.
Neural Comput., 1994

Limits in Learning Machine Accuracy Imposed by Data Quality.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Comparison of classifier methods: a case study in handwritten digit recognition.
Proceedings of the 12th IAPR International Conference on Pattern Recognition, 1994

Boosting and Other Machine Learning Algorithms.
Proceedings of the Machine Learning, 1994

1993
Learning Curves: Asymptotic Values and Rate of Convergence.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993


  Loading...