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ORCIDBorja Balle
Borja de Balle Pigem
Person information
- affiliation: Amazon Research, Cambridge, UK
- affiliation: Lancaster University, Department of Mathematics and Statistics, UK
- affiliation: McGill University, Reasoning and Learning Laboratory, Montreal, Québec, Canada
- affiliation: Polytechnic University of Catalonia, Spain
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2020 – today
- 2026
[c58]Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Jamie Hayes, Emiliano De Cristofaro:
To Shuffle or not to Shuffle: Auditing DP-SGD with Shuffling. NDSS 2026- [i60]Ryan McKenna, Galen Andrew, Borja Balle, Vadym Doroshenko, Arun Ganesh, Weiwei Kong, Alex Kurakin, Brendan McMahan, Mikhail Pravilov:
JAX-Privacy: A library for differentially private machine learning. CoRR abs/2602.17861 (2026) - 2025
- [j18]Sahra Ghalebikesabi, Eugene Bagdasarian, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle:
Privacy Awareness for Information-Sharing Assistants: A Case-study on Form-filling with Contextual Integrity. Trans. Mach. Learn. Res. 2025 (2025) - [j17]Navodita Sharma, Vishnu Vinod, Abhradeep Guha Thakurta, Alekh Agarwal, Borja Balle, Christoph Dann, Aravindan Raghuveer:
Preserving Expert-Level Privacy in Offline Reinforcement Learning. Trans. Mach. Learn. Res. 2025 (2025) - [c57]Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni:
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. ICLR 2025 - [c56]Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis:
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. ICLR 2025 - [c55]Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang:
Scaling Laws for Differentially Private Language Models. ICML 2025 - [c54]Bogdan Kulynych, Juan Felipe Gómez, Georgios Kaissis, Jamie Hayes, Borja Balle, Flávio P. Calmon, Jean Louis Raisaro:
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy. NeurIPS 2025 - [c53]Borja Balle, James Bell-Clark, Albert Cheu, Adrià Gascón, Jonathan Katz, Mariana Raykova, Phillipp Schoppmann, Thomas Steinke:
Hash-Prune-Invert: Improved Differentially Private Heavy-Hitter Detection in the Two-Server Model. SP 2025: 2903-2918 - [i59]Ilia Shumailov, Daniel Ramage, Sarah Meiklejohn, Peter Kairouz, Florian Hartmann, Borja Balle, Eugene Bagdasarian:
Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography. CoRR abs/2501.08970 (2025) - [i58]Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang:
Scaling Laws for Differentially Private Language Models. CoRR abs/2501.18914 (2025) - [i57]Juan Felipe Gómez, Bogdan Kulynych, Georgios Kaissis, Jamie Hayes, Borja Balle, Antti Honkela:
(ϵ, δ) Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees. CoRR abs/2503.10945 (2025) - [i56]Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Jamie Hayes, Georgios Kaissis, Emiliano De Cristofaro:
The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing. CoRR abs/2506.16666 (2025) - [i55]Bogdan Kulynych, Juan Felipe Gómez, Georgios Kaissis, Jamie Hayes, Borja Balle, Flávio P. Calmon, Jean Louis Raisaro:
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy. CoRR abs/2507.06969 (2025) - [i54]Marika Swanberg, Meenatchi Sundaram Muthu Selva Annamalai, Jamie Hayes, Borja Balle, Adam D. Smith:
Beyond the Worst Case: Extending Differential Privacy Guarantees to Realistic Adversaries. CoRR abs/2507.08158 (2025) - [i53]Amer Sinha, Thomas Mesnard, Ryan McKenna, Daogao Liu, Christopher A. Choquette-Choo, Yangsibo Huang, Da Yu, Georgios Kaissis, Zachary Charles, Ruibo Liu, Lynn Chua, Pritish Kamath, Pasin Manurangsi, Steve He, Chiyuan Zhang, Badih Ghazi, Borja de Balle Pigem, Prem Eruvbetine, Tris Warkentin, Armand Joulin, Ravi Kumar:
VaultGemma: A Differentially Private Gemma Model. CoRR abs/2510.15001 (2025) - 2024
- [j16]Clara Lacroce
, Borja Balle, Prakash Panangaden, Guillaume Rabusseau:
Optimal approximate minimization of one-letter weighted finite automata. Math. Struct. Comput. Sci. 34(8): 807-833 (2024) - [j15]Sumanth Dathathri, Abigail See, Sumedh Ghaisas, Po-Sen Huang, Rob McAdam, Johannes Welbl, Vandana Bachani, Alex Kaskasoli, Robert Stanforth, Tatiana Matejovicova, Jamie Hayes, Nidhi Vyas, Majd Al Merey, Jonah Brown-Cohen, Rudy Bunel, Borja Balle, A. Taylan Cemgil, Zahra Ahmed, Kitty Stacpoole, Ilia Shumailov, Ciprian Baetu, Sven Gowal, Demis Hassabis, Pushmeet Kohli:
Scalable watermarking for identifying large language model outputs. Nat. 634(8035): 818-823 (2024) - [c52]Jonathan Lebensold, Doina Precup, Borja Balle:
On the Privacy of Selection Mechanisms with Gaussian Noise. AISTATS 2024: 1495-1503 - [c51]Eugene Bagdasarian, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage:
AirGapAgent: Protecting Privacy-Conscious Conversational Agents. CCS 2024: 3868-3882 - [c50]Georgios Kaissis, Stefan Kolek, Borja Balle, Jamie Hayes, Daniel Rueckert:
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. ICML 2024: 22840-22860 - [i52]Jonathan Lebensold, Doina Precup, Borja Balle:
On the Privacy of Selection Mechanisms with Gaussian Noise. CoRR abs/2402.06137 (2024) - [i51]Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomasev, Ira Ktena, Zachary Kenton, Mikel Rodriguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sébastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agüera y Arcas, William Isaac, James Manyika:
The Ethics of Advanced AI Assistants. CoRR abs/2404.16244 (2024) - [i50]Eugene Bagdasaryan, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage:
Air Gap: Protecting Privacy-Conscious Conversational Agents. CoRR abs/2405.05175 (2024) - [i49]Georgios Kaissis, Stefan Kolek, Borja Balle, Jamie Hayes, Daniel Rueckert:
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. CoRR abs/2406.08918 (2024) - [i48]Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle:
Operationalizing Contextual Integrity in Privacy-Conscious Assistants. CoRR abs/2408.02373 (2024) - [i47]Zhao Cheng, Diane Wan, Matthew Abueg, Sahra Ghalebikesabi, Ren Yi, Eugene Bagdasarian, Borja Balle, Stefan Mellem, Shawn O'Banion:
CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Data. CoRR abs/2409.13903 (2024) - [i46]Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni:
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. CoRR abs/2410.03883 (2024) - [i45]Thomas Steinke, Milad Nasr, Arun Ganesh, Borja Balle, Christopher A. Choquette-Choo, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis:
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. CoRR abs/2410.06186 (2024) - [i44]Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Emiliano De Cristofaro, Jamie Hayes:
To Shuffle or not to Shuffle: Auditing DP-SGD with Shuffling. CoRR abs/2411.10614 (2024) - [i43]Navodita Sharma, Vishnu Vinod, Abhradeep Thakurta, Alekh Agarwal, Borja Balle, Christoph Dann, Aravindan Raghuveer:
Preserving Expert-Level Privacy in Offline Reinforcement Learning. CoRR abs/2411.13598 (2024) - [i42]Borja Balle, James Bell, Albert Cheu, Adrià Gascón, Jonathan Katz, Mariana Raykova, Phillipp Schoppmann, Thomas Steinke:
Hash-Prune-Invert: Improved Differentially Private Heavy-Hitter Detection in the Two-Server Model. IACR Cryptol. ePrint Arch. 2024: 2024 (2024) - 2023
- [c49]Borja Balle, James Bell, Adrià Gascón:
Amplification by Shuffling without Shuffling. CCS 2023: 2292-2305 - [c48]Jamie Hayes, Borja Balle, Saeed Mahloujifar:
Bounding training data reconstruction in DP-SGD. NeurIPS 2023 - [c47]Ali Shahin Shamsabadi, Jamie Hayes, Borja Balle, Adrian Weller:
Mnemonist: Locating Model Parameters that Memorize Training Examples. UAI 2023: 1879-1888 - [c46]Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, Andreas Terzis:
Tight Auditing of Differentially Private Machine Learning. USENIX Security Symposium 2023: 1631-1648 - [c45]Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace:
Extracting Training Data from Diffusion Models. USENIX Security Symposium 2023: 5253-5270 - [i41]David W. Archer, Borja de Balle Pigem, Dan Bogdanov, Mark Craddock, Adrià Gascón, Ronald Jansen, Matjaz Jug, Kim Laine, Robert McLellan, Olga Ohrimenko, Mariana Raykova, Andrew Trask, Simon Wardley:
UN Handbook on Privacy-Preserving Computation Techniques. CoRR abs/2301.06167 (2023) - [i40]Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace:
Extracting Training Data from Diffusion Models. CoRR abs/2301.13188 (2023) - [i39]Jamie Hayes, Saeed Mahloujifar, Borja Balle:
Bounding Training Data Reconstruction in DP-SGD. CoRR abs/2302.07225 (2023) - [i38]Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, Andreas Terzis:
Tight Auditing of Differentially Private Machine Learning. CoRR abs/2302.07956 (2023) - [i37]Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle:
Differentially Private Diffusion Models Generate Useful Synthetic Images. CoRR abs/2302.13861 (2023) - [i36]Borja Balle, James Bell, Adrià Gascón:
Amplification by Shuffling without Shuffling. CoRR abs/2305.10867 (2023) - [i35]Clara Lacroce, Borja Balle, Prakash Panangaden, Guillaume Rabusseau:
Optimal Approximate Minimization of One-Letter Weighted Finite Automata. CoRR abs/2306.00135 (2023) - [i34]Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle:
Unlocking Accuracy and Fairness in Differentially Private Image Classification. CoRR abs/2308.10888 (2023) - 2022
- [j14]Borja Balle, Pascale Gourdeau, Prakash Panangaden:
Bisimulation metrics and norms for real-weighted automata. Inf. Comput. 282: 104649 (2022) - [j13]Borja Balle, Guillaume Rabusseau:
Approximate minimization of weighted tree automata. Inf. Comput. 282: 104654 (2022) - [c44]Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, Iason Gabriel:
Taxonomy of Risks posed by Language Models. FAccT 2022: 214-229 - [c43]Borja Balle, Giovanni Cherubin, Jamie Hayes:
Reconstructing Training Data with Informed Adversaries. SP 2022: 1138-1156 - [i33]Jamie Hayes, Borja Balle, M. Pawan Kumar:
Learning to be adversarially robust and differentially private. CoRR abs/2201.02265 (2022) - [i32]Borja Balle, Giovanni Cherubin, Jamie Hayes:
Reconstructing Training Data with Informed Adversaries. CoRR abs/2201.04845 (2022) - [i31]Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle:
Unlocking High-Accuracy Differentially Private Image Classification through Scale. CoRR abs/2204.13650 (2022) - 2021
- [c42]Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup, Guillaume Rabusseau:
Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. ICALP 2021: 118:1-118:20 - [i30]Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup, Guillaume Rabusseau:
Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. CoRR abs/2102.06860 (2021) - [i29]Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William Isaac, Sean Legassick, Geoffrey Irving, Iason Gabriel:
Ethical and social risks of harm from Language Models. CoRR abs/2112.04359 (2021) - 2020
- [j12]Louigi Addario-Berry, Borja Balle, Guillem Perarnau:
Diameter and Stationary Distribution of Random $r$-Out Digraphs. Electron. J. Comb. 27(3): 3 (2020) - [j11]Borja Balle, Gilles Barthe, Marco Gaboardi:
Privacy Profiles and Amplification by Subsampling. J. Priv. Confidentiality 10(1) (2020) - [j10]Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan:
Subsampled Rényi Differential Privacy and Analytical Moments Accountant. J. Priv. Confidentiality 10(2) (2020) - [j9]Phillipp Schoppmann, Lennart Vogelsang, Adrià Gascón, Borja Balle:
Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue. Proc. Priv. Enhancing Technol. 2020(2): 209-229 (2020) - [j8]Brendan Avent, Javier González, Tom Diethe, Andrei Paleyes, Borja Balle:
Automatic Discovery of Privacy-Utility Pareto Fronts. Proc. Priv. Enhancing Technol. 2020(4): 5-23 (2020) - [c41]Amir-Hossein Karimi, Gilles Barthe, Borja Balle, Isabel Valera:
Model-Agnostic Counterfactual Explanations for Consequential Decisions. AISTATS 2020: 895-905 - [c40]Borja Balle, Gilles Barthe, Marco Gaboardi, Justin Hsu, Tetsuya Sato:
Hypothesis Testing Interpretations and Renyi Differential Privacy. AISTATS 2020: 2496-2506 - [c39]Hisham Husain, Borja Balle, Zac Cranko, Richard Nock:
Local Differential Privacy for Sampling. AISTATS 2020: 3404-3413 - [c38]Borja Balle, James Bell, Adrià Gascón, Kobbi Nissim:
Private Summation in the Multi-Message Shuffle Model. CCS 2020: 657-676 - [c37]Krishnamurthy (Dj) Dvijotham, Jamie Hayes, Borja Balle, J. Zico Kolter, Chongli Qin, András György, Kai Xiao, Sven Gowal, Pushmeet Kohli:
A Framework for robustness Certification of Smoothed Classifiers using F-Divergences. ICLR 2020 - [c36]Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Zhiwei Steven Wu:
Private Reinforcement Learning with PAC and Regret Guarantees. ICML 2020: 9754-9764 - [c35]Borja Balle, Peter Kairouz, Brendan McMahan, Om Dipakbhai Thakkar, Abhradeep Thakurta:
Privacy Amplification via Random Check-Ins. NeurIPS 2020 - [c34]Oluwaseyi Feyisetan, Borja Balle, Tom Diethe, Thomas Drake:
Calibrating Mechanisms for Privacy Preserving Text Analysis. PrivateNLP@WSDM 2020: 8-11 - [c33]Oluwaseyi Feyisetan, Borja Balle:
Privacy-Preserving Textual Analysis via Calibrated Perturbations. PrivateNLP@WSDM 2020: 41-42 - [c32]Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe:
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. WSDM 2020: 178-186 - [i28]Borja Balle, James Bell, Adrià Gascón, Kobbi Nissim:
Private Summation in the Multi-Message Shuffle Model. CoRR abs/2002.00817 (2020) - [i27]Borja Balle, Peter Kairouz, H. Brendan McMahan, Om Thakkar, Abhradeep Thakurta:
Privacy Amplification via Random Check-Ins. CoRR abs/2007.06605 (2020) - [i26]Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Zhiwei Steven Wu:
Private Reinforcement Learning with PAC and Regret Guarantees. CoRR abs/2009.09052 (2020)
2010 – 2019
- 2019
- [j7]Borja Balle, Prakash Panangaden, Doina Precup:
Singular value automata and approximate minimization. Math. Struct. Comput. Sci. 29(9): 1444-1478 (2019) - [c31]Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan:
Subsampled Renyi Differential Privacy and Analytical Moments Accountant. AISTATS 2019: 1226-1235 - [c30]Borja Balle, Adrià Gascón, Olya Ohrimenko, Mariana Raykova, Phillipp Schoppmann, Carmela Troncoso:
PPML '19: Privacy Preserving Machine Learning. CCS 2019: 2717-2718 - [c29]Borja Balle, James Bell, Adrià Gascón, Kobbi Nissim:
The Privacy Blanket of the Shuffle Model. CRYPTO (2) 2019: 638-667 - [c28]Borja Balle, Gilles Barthe, Marco Gaboardi, Joseph Geumlek:
Privacy Amplification by Mixing and Diffusion Mechanisms. NeurIPS 2019: 13277-13287 - [i25]Borja Balle, James Bell, Adrià Gascón, Kobbi Nissim:
The Privacy Blanket of the Shuffle Model. CoRR abs/1903.02837 (2019) - [i24]Tom Diethe, Tom Borchert, Eno Thereska, Borja Balle, Neil Lawrence:
Continual Learning in Practice. CoRR abs/1903.05202 (2019) - [i23]Oluwaseyi Feyisetan, Thomas Drake, Borja Balle, Tom Diethe:
Privacy-preserving Active Learning on Sensitive Data for User Intent Classification. CoRR abs/1903.11112 (2019) - [i22]Borja Balle, Gilles Barthe, Marco Gaboardi, Justin Hsu, Tetsuya Sato:
Hypothesis Testing Interpretations and Renyi Differential Privacy. CoRR abs/1905.09982 (2019) - [i21]Brendan Avent, Javier González, Tom Diethe, Andrei Paleyes, Borja Balle:
Automatic Discovery of Privacy-Utility Pareto Fronts. CoRR abs/1905.10862 (2019) - [i20]Amir-Hossein Karimi, Gilles Barthe, Borja Balle, Isabel Valera:
Model-Agnostic Counterfactual Explanations for Consequential Decisions. CoRR abs/1905.11190 (2019) - [i19]Borja Balle, Gilles Barthe, Marco Gaboardi, Joseph Geumlek:
Privacy Amplification by Mixing and Diffusion Mechanisms. CoRR abs/1905.12264 (2019) - [i18]Borja Balle, James Bell, Adrià Gascón, Kobbi Nissim:
Differentially Private Summation with Multi-Message Shuffling. CoRR abs/1906.09116 (2019) - [i17]Borja Balle, James Bell, Adrià Gascón, Kobbi Nissim:
Improved Summation from Shuffling. CoRR abs/1909.11225 (2019) - [i16]Jonathan Lebensold, William L. Hamilton, Borja Balle, Doina Precup:
Actor Critic with Differentially Private Critic. CoRR abs/1910.05876 (2019) - [i15]Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe:
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. CoRR abs/1910.08902 (2019) - 2018
- [j6]Borja Balle, Mehryar Mohri:
Generalization bounds for learning weighted automata. Theor. Comput. Sci. 716: 89-106 (2018) - [c27]Yuri Grinberg, Hossein Aboutalebi, Melanie Lyman-Abramovitch, Borja Balle, Doina Precup:
Learning Predictive State Representations From Non-Uniform Sampling. AAAI 2018: 3061-3068 - [c26]Borja Balle, Yu-Xiang Wang:
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising. ICML 2018: 403-412 - [c25]Borja Balle, Gilles Barthe, Marco Gaboardi:
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences. NeurIPS 2018: 6280-6290 - [i14]Borja Balle, Yu-Xiang Wang:
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising. CoRR abs/1805.06530 (2018) - [i13]Borja Balle, Gilles Barthe, Marco Gaboardi:
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences. CoRR abs/1807.01647 (2018) - [i12]Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan:
Subsampled Rényi Differential Privacy and Analytical Moments Accountant. CoRR abs/1808.00087 (2018) - [i11]Matteo Ruffini, Guillaume Rabusseau, Borja Balle:
Hierarchical Methods of Moments. CoRR abs/1810.07468 (2018) - [i10]Phillipp Schoppmann, Adrià Gascón, Borja Balle:
Private Nearest Neighbors Classification in Federated Databases. IACR Cryptol. ePrint Arch. 2018: 289 (2018) - 2017
- [j5]Adrià Gascón, Phillipp Schoppmann, Borja Balle, Mariana Raykova, Jack Doerner, Samee Zahur, David Evans:
Privacy-Preserving Distributed Linear Regression on High-Dimensional Data. Proc. Priv. Enhancing Technol. 2017(4): 345-364 (2017) - [c24]Borja Balle, Pascale Gourdeau, Prakash Panangaden:
Bisimulation Metrics for Weighted Automata. ICALP 2017: 103:1-103:14 - [c23]Borja Balle, Odalric-Ambrym Maillard:
Spectral Learning from a Single Trajectory under Finite-State Policies. ICML 2017: 361-370 - [c22]Matteo Ruffini, Guillaume Rabusseau, Borja Balle:
Hierarchical Methods of Moments. NIPS 2017: 1901-1911 - [c21]Guillaume Rabusseau, Borja Balle, Joelle Pineau:
Multitask Spectral Learning of Weighted Automata. NIPS 2017: 2588-2597 - [i9]Borja Balle, Pascale Gourdeau, Prakash Panangaden:
Bisimulation Metrics for Weighted Automata. CoRR abs/1702.08017 (2017) - [i8]Borja Balle, Prakash Panangaden, Doina Precup:
Singular value automata and approximate minimization. CoRR abs/1711.05994 (2017) - 2016
- [c20]Boyu Wang, Joelle Pineau, Borja Balle:
Multitask Generalized Eigenvalue Program. AAAI 2016: 2115-2121 - [c19]Guillaume Rabusseau, Borja Balle, Shay B. Cohen:
Low-Rank Approximation of Weighted Tree Automata. AISTATS 2016: 839-847 - [c18]Borja Balle, Rémi Eyraud, Franco M. Luque, Ariadna Quattoni, Sicco Verwer:
Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence. ICGI 2016: 132-136 - [c17]Borja Balle, Maziar Gomrokchi, Doina Precup:
Differentially Private Policy Evaluation. ICML 2016: 2130-2138 - [c16]Chenghui Zhou, Borja Balle, Joelle Pineau:
Learning time series models for pedestrian motion prediction. ICRA 2016: 3323-3330 - [c15]Lucas Langer, Borja Balle, Doina Precup:
Learning Multi-Step Predictive State Representations. IJCAI 2016: 1662-1668 - [i7]Borja Balle, Maziar Gomrokchi, Doina Precup:
Differentially Private Policy Evaluation. CoRR abs/1603.02010 (2016) - [i6]Borja Balle, Mehryar Mohri:
Generalization Bounds for Weighted Automata. CoRR abs/1610.07883 (2016) - [i5]Adrià Gascón, Phillipp Schoppmann, Borja Balle, Mariana Raykova, Jack Doerner, Samee Zahur, David Evans:
Secure Linear Regression on Vertically Partitioned Datasets. IACR Cryptol. ePrint Arch. 2016: 892 (2016) - 2015
- [c14]Borja Balle, Mehryar Mohri:
On the Rademacher Complexity of Weighted Automata. ALT 2015: 179-193 - [c13]Borja Balle, Mehryar Mohri:
Learning Weighted Automata. CAI 2015: 1-21 - [c12]Borja Balle, Prakash Panangaden, Doina Precup:
A Canonical Form for Weighted Automata and Applications to Approximate Minimization. LICS 2015: 701-712 - [c11]Pierre-Luc Bacon, Borja Balle, Doina Precup:
Learning and Planning with Timing Information in Markov Decision Processes. UAI 2015: 111-120 - [i4]Borja Balle, Prakash Panangaden, Doina Precup:
A Canonical Form for Weighted Automata and Applications to Approximate Minimization. CoRR abs/1501.06841 (2015) - [i3]Louigi Addario-Berry, Borja Balle, Guillem Perarnau:
Diameter and Stationary Distribution of Random $r$-out Digraphs. CoRR abs/1504.06840 (2015) - [i2]Guillaume Rabusseau, Borja Balle, Shay B. Cohen:
Weighted Tree Automata Approximation by Singular Value Truncation. CoRR abs/1511.01442 (2015) - 2014
- [j4]Borja Balle, Xavier Carreras, Franco M. Luque, Ariadna Quattoni:
Spectral learning of weighted automata - A forward-backward perspective. Mach. Learn. 96(1-2): 33-63 (2014) - [j3]Borja Balle, Jorge Castro, Ricard Gavaldà:
Adaptively learning probabilistic deterministic automata from data streams. Mach. Learn. 96(1-2): 99-127 (2014) - [c10]Borja Balle, William L. Hamilton, Joelle Pineau:
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison. ICML 2014: 1386-1394 - [c9]Ariadna Quattoni, Borja Balle, Xavier Carreras, Amir Globerson:
Spectral Regularization for Max-Margin Sequence Tagging. ICML 2014: 1710-1718 - 2013
- [b1]Borja Balle:
Learning finite-state machines: statistical and algorithmic aspects. Polytechnic University of Catalonia, Spain, 2013 - [j2]Borja Balle, Jorge Castro, Ricard Gavaldà:
Learning probabilistic automata: A study in state distinguishability. Theor. Comput. Sci. 473: 46-60 (2013) - [c8]Borja Balle, Bernardino Casas, Alex Catarineu, Ricard Gavaldà, David Manzano-Macho:
The Architecture of a Churn Prediction System Based on Stream Mining. CCIA 2013: 157-166 - [i1]Borja Balle:
Ergodicity of Random Walks on Random DFA. CoRR abs/1311.6830 (2013) - 2012
- [c7]Franco M. Luque, Ariadna Quattoni, Borja Balle, Xavier Carreras:
Spectral Learning for Non-Deterministic Dependency Parsing. EACL 2012: 409-419 - [c6]Borja Balle, Ariadna Quattoni, Xavier Carreras:
Local Loss Optimization in Operator Models: A New Insight into Spectral Learning. ICML 2012 - [c5]Borja Balle, Mehryar Mohri:
Spectral Learning of General Weighted Automata via Constrained Matrix Completion. NIPS 2012: 2168-2176 - [c4]Borja Balle, Jorge Castro, Ricard Gavaldà:
Bootstrapping and Learning PDFA in Data Streams. ICGI 2012: 34-48 - 2011
- [c3]Borja Balle, Ariadna Quattoni, Xavier Carreras:
A Spectral Learning Algorithm for Finite State Transducers. ECML/PKDD (1) 2011: 156-171 - 2010
- [c2]Borja Balle, Jorge Castro, Ricard Gavaldà:
A Lower Bound for Learning Distributions Generated by Probabilistic Automata. ALT 2010: 179-193 - [c1]Borja Balle, Jorge Castro, Ricard Gavaldà:
Learning PDFA with Asynchronous Transitions. ICGI 2010: 271-275
2000 – 2009
- 2008
- [j1]Josep M. Fuertes, Borja Balle, Enric Ventura:
Absolute-Type Shaft Encoding Using LFSR Sequences With a Prescribed Length. IEEE Trans. Instrum. Meas. 57(5): 915-922 (2008)
Coauthor Index
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