Mehryar Mohri

Orcid: 0000-0002-3987-9847

Affiliations:
  • New York University, Courant Institute of Mathematical Sciences, USA
  • Google Research


According to our database1, Mehryar Mohri authored at least 262 papers between 1994 and 2024.

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Bibliography

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

Regression with Multi-Expert Deferral.
CoRR, 2024

H-Consistency Guarantees for Regression.
CoRR, 2024

2023
Principled Approaches for Learning to Defer with Multiple Experts.
CoRR, 2023

Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms.
CoRR, 2023

Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention.
CoRR, 2023

Ranking with Abstention.
CoRR, 2023

Differentially Private Domain Adaptation with Theoretical Guarantees.
CoRR, 2023

Best-Effort Adaptation.
CoRR, 2023

Two-Stage Learning to Defer with Multiple Experts.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Structured Prediction with Stronger Consistency Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

H-Consistency Bounds: Characterization and Extensions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cross-Entropy Loss Functions: Theoretical Analysis and Applications.
Proceedings of the International Conference on Machine Learning, 2023

H-Consistency Bounds for Pairwise Misranking Loss Surrogates.
Proceedings of the International Conference on Machine Learning, 2023

Reinforcement Learning Can Be More Efficient with Multiple Rewards.
Proceedings of the International Conference on Machine Learning, 2023

Pseudonorm Approachability and Applications to Regret Minimization.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Principled Approaches for Private Adaptation from a Public Source.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Private Domain Adaptation from a Public Source.
CoRR, 2022

H-Consistency Estimation Error of Surrogate Loss Minimizers.
CoRR, 2022

Multiple-source adaptation theory and algorithms - addendum.
Ann. Math. Artif. Intell., 2022

Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differentially Private Learning with Margin Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-Class $H$-Consistency Bounds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation.
Proceedings of the International Conference on Machine Learning, 2022

H-Consistency Bounds for Surrogate Loss Minimizers.
Proceedings of the International Conference on Machine Learning, 2022

Strategizing against Learners in Bayesian Games.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Advances and Open Problems in Federated Learning.
Found. Trends Mach. Learn., 2021

On the Existence of the Adversarial Bayes Classifier (Extended Version).
CoRR, 2021

A Field Guide to Federated Optimization.
CoRR, 2021

A Finer Calibration Analysis for Adversarial Robustness.
CoRR, 2021

Multiple-source adaptation theory and algorithms.
Ann. Math. Artif. Intell., 2021

Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning with User-Level Privacy.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Breaking the centralized barrier for cross-device federated learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Calibration and Consistency of Adversarial Surrogate Losses.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Existence of The Adversarial Bayes Classifier.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Communication-Efficient Agnostic Federated Averaging.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 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

A Theory of Multiple-Source Adaptation with Limited Target Labeled Data.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Corralling Stochastic Bandit Algorithms.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

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

Beyond Individual and Group Fairness.
CoRR, 2020

Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning.
CoRR, 2020

On the Rademacher Complexity of Linear Hypothesis Sets.
CoRR, 2020

A Theory of Multiple-Source Adaptation with Limited Target Labeled Data.
CoRR, 2020

Three Approaches for Personalization with Applications to Federated Learning.
CoRR, 2020

Discrepancy-Based Theory and Algorithms for Forecasting Non-Stationary Time Series.
Ann. Math. Artif. Intell., 2020

Adapting to Misspecification in Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Reinforcement Learning with Feedback Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

PAC-Bayes Learning Bounds for Sample-Dependent Priors.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

FedBoost: A Communication-Efficient Algorithm for Federated Learning.
Proceedings of the 37th International Conference on Machine Learning, 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

Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

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

Advances and Open Problems in Federated Learning.
CoRR, 2019

SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning.
CoRR, 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

Hypothesis Set Stability and Generalization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

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

Bandits with Feedback Graphs and Switching Costs.
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

Agnostic Federated Learning.
Proceedings of the 36th International Conference on Machine Learning, 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
Generalization bounds for learning weighted automata.
Theor. Comput. Sci., 2018

Theory and Algorithms for Forecasting Time Series.
CoRR, 2018

Algorithms and Theory for Multiple-Source Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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

Policy Regret in Repeated Games.
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

Logistic Regression: The Importance of Being Improper.
Proceedings of the Conference On Learning Theory, 2018

Competing with Automata-based Expert Sequences.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
A disambiguation algorithm for weighted automata.
Theor. Comput. Sci., 2017

Generalization bounds for non-stationary mixing processes.
Mach. Learn., 2017

Multiple-Source Adaptation for Regression Problems.
CoRR, 2017

Online Learning with Expert Automata.
CoRR, 2017

On-line Learning with Abstention.
CoRR, 2017

Online Learning with Transductive Regret.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Discriminative State Space Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Parameter-Free Online Learning via Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

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

2016
Learning Algorithms for Second-Price Auctions with Reserve.
J. Mach. Learn. Res., 2016

Structured Prediction Theory and Voted Risk Minimization.
CoRR, 2016

Generalization Bounds for Weighted Automata.
CoRR, 2016

Adaptive Algorithms and Data-Dependent Guarantees for Bandit Convex Optimization.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Optimistic Bandit Convex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 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 N-Gram Language Models from Uncertain Data.
Proceedings of the Interspeech 2016, 2016

Time series prediction and online learning.
Proceedings of the 29th Conference on Learning Theory, 2016

Structural Online Learning.
Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

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

Accelerating Online Convex Optimization via Adaptive Prediction.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Random Composite Forests.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Foundations of Coupled Nonlinear Dimensionality Reduction.
CoRR, 2015

Accelerating Optimization via Adaptive Prediction.
CoRR, 2015

Voted Kernel Regularization.
CoRR, 2015

On the Disambiguation of Weighted Automata.
Proceedings of the Implementation and Application of Automata, 2015

Non-parametric Revenue Optimization for Generalized Second Price auctions..
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Generalization Bounds for Supervised Dimensionality Reduction.
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

Revenue Optimization against Strategic Buyers.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Learning Theory and Algorithms for Forecasting Non-stationary Time Series.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 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

Automata and graph compression.
Proceedings of the IEEE International Symposium on Information Theory, 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

Learning Weighted Automata.
Proceedings of the Algebraic Informatics - 6th International Conference, 2015

Learning with Deep Cascades.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

On the Rademacher Complexity of Weighted Automata.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

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

Revenue Optimization in Posted-Price Auctions with Strategic Buyers.
CoRR, 2014

Conditional Swap Regret and Conditional Correlated Equilibrium.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Multi-Class Deep Boosting.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Corporate learning at scale: lessons from a large online course at google.
Proceedings of the First (2014) ACM Conference on Learning @ Scale, 2014

Learning Theory and Algorithms for revenue optimization in second price auctions with reserve.
Proceedings of the 31th International Conference on Machine Learning, 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

Generalization Bounds for Time Series Prediction with Non-stationary Processes.
Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014

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

2013
Large-scale SVD and manifold learning.
J. Mach. Learn. Res., 2013

On the Disambiguation of Finite Automata and Functional Transducers.
Int. J. Found. Comput. Sci., 2013

Perceptron Mistake Bounds
CoRR, 2013

Tight Lower Bound on the Probability of a Binomial Exceeding its Expectation.
CoRR, 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
Sampling Methods for the Nyström Method.
J. Mach. Learn. Res., 2012

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

A Disambiguation Algorithm for Finite Automata and Functional Transducers.
Proceedings of the Implementation and Application of Automata, 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

Spectral Learning of General Weighted Automata via Constrained Matrix Completion.
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

New Analysis and Algorithm for Learning with Drifting Distributions.
Proceedings of the Algorithmic Learning Theory - 23rd International Conference, 2012

Foundations of Machine Learning.
Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-01825-8, 2012

2011
Can matrix coherence be efficiently and accurately estimated?
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

General Algorithms for Testing the Ambiguity of Finite Automata and the Double-Tape Ambiguity of Finite-State Transducers.
Int. J. Found. Comput. Sci., 2011

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

Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081).
Dagstuhl Reports, 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
Efficient and Robust Music Identification With Weighted Finite-State Transducers.
IEEE Trans. Speech Audio Process., 2010

Preference-based learning to rank.
Mach. Learn., 2010

Stability Bounds for Stationary phi-mixing and beta-mixing Processes.
J. Mach. Learn. Res., 2010

Discriminative Topic Segmentation of Text and Speech.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 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

On the Estimation of Coherence
CoRR, 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

Expected Sequence Similarity Maximization.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 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
General suffix automaton construction algorithm and space bounds.
Theor. Comput. Sci., 2009

Sampling Techniques for the Nystrom Method.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Gaussian Margin Machines.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

N-Way Composition of Weighted Finite-State Transducers.
Int. J. Found. Comput. Sci., 2009

New Generalization Bounds for Learning Kernels
CoRR, 2009

Linear-Space Computation of the Edit-Distance between a String and a Finite Automaton
CoRR, 2009

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

Multiple Source Adaptation and the Rényi Divergence.
Proceedings of the UAI 2009, 2009

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

Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models.
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

Ensemble Nystrom Method.
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

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

A new quality measure for topic segmentation of text and speech.
Proceedings of the INTERSPEECH 2009, 2009

On sampling-based approximate spectral decomposition.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Domain Adaptation: Learning Bounds and Algorithms.
Proceedings of the COLT 2009, 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 Bound for Stationary Phi-mixing and Beta-mixing Processes
CoRR, 2008

3-Way Composition of Weighted Finite-State Transducers.
Proceedings of the Implementation and Applications of Automata, 2008

Rademacher Complexity Bounds for Non-I.I.D. Processes.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Domain Adaptation with Multiple Sources.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

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

Sequence kernels for predicting protein essentiality.
Proceedings of the Machine Learning, 2008

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

General Algorithms for Testing the Ambiguity of Finite Automata.
Proceedings of the Developments in Language Theory, 12th International Conference, 2008

An Efficient Reduction of Ranking to Classification.
Proceedings of the 21st Annual Conference on Learning Theory, 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

Factor Automata of Automata and Applications.
Proceedings of the Implementation and Application of Automata, 2007

OpenFst: A General and Efficient Weighted Finite-State Transducer Library.
Proceedings of the Implementation and Application of Automata, 2007

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

Stability Bounds for Non-i.i.d. Processes.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Robust Music Identification, Detection, and Analysis.
Proceedings of the 8th International Conference on Music Information Retrieval, 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

Probabilistic Context-Free Grammar Induction Based on Structural Zeros.
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, 2006

A Unified Construction of the Glushkov, Follow, and Antimirov Automata.
Proceedings of the Mathematical Foundations of Computer Science 2006, 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

The design principles and algorithms of a weighted grammar library.
Int. J. Found. Comput. Sci., 2005

Weighted Automata in Text and Speech Processing
CoRR, 2005

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

A Comparison of Classifiers for Detecting Emotion from Speech.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Multi-armed Bandit Algorithms and Empirical Evaluation.
Proceedings of the Machine Learning: ECML 2005, 2005

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

2004
An optimal pre-determinization algorithm for weighted transducers.
Theor. Comput. Sci., 2004

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

A General Weighted Grammar Library.
Proceedings of the Implementation and Application of Automata, 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

A generalized construction of integrated speech recognition transducers.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Statistical Modeling for Unit Selection in Speech Synthesis.
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, 2004

2003
Efficient Algorithms for Testing the Twins Property.
J. Autom. Lang. Comb., 2003

Edit-Distance Of Weighted Automata: General Definitions And Algorithms.
Int. J. Found. Comput. Sci., 2003

Finitely Subsequential Transducers.
Int. J. Found. Comput. Sci., 2003

An Efficient Pre-determinization Algorithm.
Proceedings of the Implementation and Application of Automata, 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

Generalized optimization algorithm for speech recognition transducers.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Learning from Uncertain Data.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

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

Generalized Algorithms for Constructing Statistical Language Models.
Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics, 2003

2002
Semiring Frameworks and Algorithms for Shortest-Distance Problems.
J. Autom. Lang. Comb., 2002

Generic e-Removal and Input e-Normalization Algorithms for Weighted Transducers.
Int. J. Found. Comput. Sci., 2002

Weighted finite-state transducers in speech recognition.
Comput. Speech Lang., 2002

Edit-Distance of Weighted Automata.
Proceedings of the Implementation and Application of Automata, 2002

p-Subsequentiable Transducers.
Proceedings of the Implementation and Application of Automata, 2002

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

An efficient algorithm for the n-best-strings problem.
Proceedings of the 7th International Conference on Spoken Language Processing, ICSLP2002, 2002

A comparison of two LVR search optimization techniques.
Proceedings of the 7th International Conference on Spoken Language Processing, ICSLP2002, 2002

2001
A weight pushing algorithm for large vocabulary speech recognition.
Proceedings of the EUROSPEECH 2001 Scandinavia, 2001

2000
The Design Principles of a Weighted Finite-State Transducer Library.
Theor. Comput. Sci., 2000

Minimization algorithms for sequential transducers.
Theor. Comput. Sci., 2000

Context-Free Recognition with Weighted Automata.
Grammars, 2000

Generic epsilon -Removal Algorithm for Weighted Automata.
Proceedings of the Implementation and Application of Automata, 2000

1999
Network optimizations for large-vocabulary speech recognition.
Speech Commun., 1999

Integrated context-dependent networks in very large vocabulary speech recognition.
Proceedings of the Sixth European Conference on Speech Communication and Technology, 1999

Rapid unit selection from a large speech corpus for concatenative speech synthesis.
Proceedings of the Sixth European Conference on Speech Communication and Technology, 1999

1998
VPQ: a spoken language interface to large scale directory information.
Proceedings of the 5th International Conference on Spoken Language Processing, Incorporating The 7th Australian International Speech Science and Technology Conference, Sydney Convention Centre, Sydney, Australia, 30th November, 1998

Full expansion of context-dependent networks in large vocabulary speech recognition.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

Dynamic Compilation of Weighted Context-Free Grammars.
Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, 1998

1997
String-Matching with Automata.
Nord. J. Comput., 1997

Finite-State Transducers in Language and Speech Processing.
Comput. Linguistics, 1997

A Rational Design for a Weighted Finite-State Transducer Library.
Proceedings of the Automata Implementation, 1997

Transducer composition for context-dependent network expansion.
Proceedings of the Fifth European Conference on Speech Communication and Technology, 1997

Weighted determinization and minimization for large vocabulary speech recognition.
Proceedings of the Fifth European Conference on Speech Communication and Technology, 1997

1996
On some applications of finite-state automata theory to natural language processing.
Nat. Lang. Eng., 1996

Algorithms for Speech Recognition and Language Processing
CoRR, 1996

An Efficient Compiler for Weighted Rewrite Rules.
Proceedings of the 34th Annual Meeting of the Association for Computational Linguistics, 1996

1995
Computation of French Temporal Expressions to Query Databases.
Proceedings of the First International Workshop on Applications of Natural Language to Data Bases, 1995

Matching Patterns of An Automaton.
Proceedings of the Combinatorial Pattern Matching, 6th Annual Symposium, 1995

1994
Syntactic Analysis by Local Grammars Automata: an Efficient Algorithm.
CoRR, 1994

Minimization of Sequential Transducers.
Proceedings of the Combinatorial Pattern Matching, 5th Annual Symposium, 1994

Compact Representations by Finite-State Transducers.
Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, 1994


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