Borja Balle

According to our database1, Borja Balle authored at least 61 papers between 2008 and 2020.

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Bibliography

2020
Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue.
Proc. Priv. Enhancing Technol., 2020

Automatic Discovery of Privacy-Utility Pareto Fronts.
Proc. Priv. Enhancing Technol., 2020

Private Reinforcement Learning with PAC and Regret Guarantees.
CoRR, 2020

Privacy Amplification via Random Check-Ins.
CoRR, 2020

Diameter and Stationary Distribution of Random $r$-Out Digraphs.
Electron. J. Comb., 2020

Calibrating Mechanisms for Privacy Preserving Text Analysis.
Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Privacy-Preserving Textual Analysis via Calibrated Perturbations.
Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

A Framework for robustness Certification of Smoothed Classifiers using F-Divergences.
Proceedings of the 8th International Conference on Learning Representations, 2020

Private Summation in the Multi-Message Shuffle Model.
Proceedings of the CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security, 2020

Model-Agnostic Counterfactual Explanations for Consequential Decisions.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Local Differential Privacy for Sampling.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Hypothesis Testing Interpretations and Renyi Differential Privacy.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Singular value automata and approximate minimization.
Math. Struct. Comput. Sci., 2019

Actor Critic with Differentially Private Critic.
CoRR, 2019

Improved Summation from Shuffling.
CoRR, 2019

Differentially Private Summation with Multi-Message Shuffling.
CoRR, 2019

Privacy-preserving Active Learning on Sensitive Data for User Intent Classification.
CoRR, 2019

Continual Learning in Practice.
CoRR, 2019

Privacy Amplification by Mixing and Diffusion Mechanisms.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The Privacy Blanket of the Shuffle Model.
Proceedings of the Advances in Cryptology - CRYPTO 2019, 2019

PPML '19: Privacy Preserving Machine Learning.
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

Subsampled Renyi Differential Privacy and Analytical Moments Accountant.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Generalization bounds for learning weighted automata.
Theor. Comput. Sci., 2018

Private Nearest Neighbors Classification in Federated Databases.
IACR Cryptol. ePrint Arch., 2018

Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Predictive State Representations From Non-Uniform Sampling.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Privacy-Preserving Distributed Linear Regression on High-Dimensional Data.
Proc. Priv. Enhancing Technol., 2017

Hierarchical Methods of Moments.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multitask Spectral Learning of Weighted Automata.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Spectral Learning from a Single Trajectory under Finite-State Policies.
Proceedings of the 34th International Conference on Machine Learning, 2017

Bisimulation Metrics for Weighted Automata.
Proceedings of the 44th International Colloquium on Automata, Languages, and Programming, 2017

2016
Secure Linear Regression on Vertically Partitioned Datasets.
IACR Cryptol. ePrint Arch., 2016

Generalization Bounds for Weighted Automata.
CoRR, 2016

Learning Multi-Step Predictive State Representations.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning time series models for pedestrian motion prediction.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Differentially Private Policy Evaluation.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence.
Proceedings of the 13th International Conference on Grammatical Inference, 2016

Low-Rank Approximation of Weighted Tree Automata.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Multitask Generalized Eigenvalue Program.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Weighted Tree Automata Approximation by Singular Value Truncation.
CoRR, 2015

Learning and Planning with Timing Information in Markov Decision Processes.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

A Canonical Form for Weighted Automata and Applications to Approximate Minimization.
Proceedings of the 30th Annual ACM/IEEE Symposium on Logic in Computer Science, 2015

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

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

2014
Spectral learning of weighted automata - A forward-backward perspective.
Mach. Learn., 2014

Adaptively learning probabilistic deterministic automata from data streams.
Mach. Learn., 2014

Spectral Regularization for Max-Margin Sequence Tagging.
Proceedings of the 31th International Conference on Machine Learning, 2014

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Learning probabilistic automata: A study in state distinguishability.
Theor. Comput. Sci., 2013

Ergodicity of Random Walks on Random DFA.
CoRR, 2013

The Architecture of a Churn Prediction System Based on Stream Mining.
Proceedings of the Artificial Intelligence Research and Development, 2013

2012
Bootstrapping and Learning PDFA in Data Streams.
Proceedings of the Eleventh International Conference on Grammatical Inference, 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

Local Loss Optimization in Operator Models: A New Insight into Spectral Learning.
Proceedings of the 29th International Conference on Machine Learning, 2012

Spectral Learning for Non-Deterministic Dependency Parsing.
Proceedings of the EACL 2012, 2012

2011
A Spectral Learning Algorithm for Finite State Transducers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010
Learning PDFA with Asynchronous Transitions.
Proceedings of the Grammatical Inference: Theoretical Results and Applications, 2010

A Lower Bound for Learning Distributions Generated by Probabilistic Automata.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2008
Absolute-Type Shaft Encoding Using LFSR Sequences With a Prescribed Length.
IEEE Trans. Instrum. Meas., 2008


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