Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Private Reinforcement Learning with PAC and Regret Guarantees

Sep 18, 2020
Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Zhiwei Steven Wu


  Access Paper or Ask Questions

Privacy Amplification via Random Check-Ins

Jul 30, 2020
Borja Balle, Peter Kairouz, H. Brendan McMahan, Om Thakkar, Abhradeep Thakurta

* Updated proof for $(\epsilon_0, \delta_0)$-DP local randomizers 

  Access Paper or Ask Questions

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations

Oct 20, 2019
Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe

* Accepted at WSDM 2020 

  Access Paper or Ask Questions

Actor Critic with Differentially Private Critic

Oct 14, 2019
Jonathan Lebensold, William Hamilton, Borja Balle, Doina Precup

* 6 Pages, Presented at the Privacy in Machine Learning Workshop, NeurIPS 2019 

  Access Paper or Ask Questions

Differentially Private Summation with Multi-Message Shuffling

Jun 24, 2019
Borja Balle, James Bell, Adria Gascon, Kobbi Nissim


  Access Paper or Ask Questions

Privacy Amplification by Mixing and Diffusion Mechanisms

May 29, 2019
Borja Balle, Gilles Barthe, Marco Gaboardi, Joseph Geumlek


  Access Paper or Ask Questions

Model-Agnostic Counterfactual Explanations for Consequential Decisions

May 28, 2019
Amir-Hossein Karimi, Gilles Barthe, Borja Balle, Isabel Valera


  Access Paper or Ask Questions

Automatic Discovery of Privacy-Utility Pareto Fronts

May 26, 2019
Brendan Avent, Javier Gonzalez, Tom Diethe, Andrei Paleyes, Borja Balle


  Access Paper or Ask Questions

Hypothesis Testing Interpretations and Renyi Differential Privacy

May 24, 2019
Borja Balle, Gilles Barthe, Marco Gaboardi, Justin Hsu, Tetsuya Sato


  Access Paper or Ask Questions

Privacy-preserving Active Learning on Sensitive Data for User Intent Classification

Mar 26, 2019
Oluwaseyi Feyisetan, Thomas Drake, Borja Balle, Tom Diethe

* To appear at PAL: Privacy-Enhancing Artificial Intelligence and Language Technologies as part of the AAAI Spring Symposium Series (AAAI-SSS 2019) 

  Access Paper or Ask Questions

Continual Learning in Practice

Mar 18, 2019
Tom Diethe, Tom Borchert, Eno Thereska, Borja Balle, Neil Lawrence

* Presented at the NeurIPS 2018 workshop on Continual Learning https://sites.google.com/view/continual2018/home 

  Access Paper or Ask Questions

The Privacy Blanket of the Shuffle Model

Mar 07, 2019
Borja Balle, James Bell, Adria Gascon, Kobbi Nissim


  Access Paper or Ask Questions

Hierarchical Methods of Moments

Oct 17, 2018
Matteo Ruffini, Guillaume Rabusseau, Borja Balle

* NIPS 2017 

  Access Paper or Ask Questions

Subsampled Rényi Differential Privacy and Analytical Moments Accountant

Jul 31, 2018
Yu-Xiang Wang, Borja Balle, Shiva Kasiviswanathan


  Access Paper or Ask Questions

Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences

Jul 04, 2018
Borja Balle, Gilles Barthe, Marco Gaboardi


  Access Paper or Ask Questions

Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising

Jun 07, 2018
Borja Balle, Yu-Xiang Wang

* To appear at the 35th International Conference on Machine Learning (ICML), 2018 

  Access Paper or Ask Questions

Generalization Bounds for Weighted Automata

Oct 25, 2016
Borja Balle, Mehryar Mohri


  Access Paper or Ask Questions

Differentially Private Policy Evaluation

Mar 07, 2016
Borja Balle, Maziar Gomrokchi, Doina Precup


  Access Paper or Ask Questions

Low-Rank Approximation of Weighted Tree Automata

Dec 24, 2015
Guillaume Rabusseau, Borja Balle, Shay B. Cohen

* To appear in AISTATS 2016 

  Access Paper or Ask Questions

Local Loss Optimization in Operator Models: A New Insight into Spectral Learning

Jun 27, 2012
Borja Balle, Ariadna Quattoni, Xavier Carreras

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

  Access Paper or Ask Questions