Absolute-Type Shaft Encoding Using LFSR Sequences With a Prescribed Length. - Josep M. Fuertes; Borja Balle; Enric Ventura (IEEE Trans. Instrum. Meas., 2008)

A Lower Bound for Learning Distributions Generated by Probabilistic Automata. - Borja Balle; Jorge Castro; Ricard Gavaldà (ALT, 2010)

Learning PDFA with Asynchronous Transitions. - Borja Balle; Jorge Castro; Ricard Gavaldà (ICGI, 2010)

A Spectral Learning Algorithm for Finite State Transducers. - Borja Balle; Ariadna Quattoni; Xavier Carreras (ECML/PKDD (1), 2011)

Spectral Learning for Non-Deterministic Dependency Parsing. - Franco M. Luque; Ariadna Quattoni; Borja Balle; Xavier Carreras (EACL, 2012)

Local Loss Optimization in Operator Models: A New Insight into Spectral Learning. - Borja Balle; Ariadna Quattoni; Xavier Carreras (ICML, 2012)

Spectral Learning of General Weighted Automata via Constrained Matrix Completion. - Borja Balle; Mehryar Mohri (NIPS, 2012)

Bootstrapping and Learning PDFA in Data Streams. - Borja Balle; Jorge Castro; Ricard Gavaldà (ICGI, 2012)

The Architecture of a Churn Prediction System Based on Stream Mining. - Borja Balle; Bernardino Casas; Alex Catarineu; Ricard Gavaldà; David Manzano-Macho (CCIA, 2013)

Ergodicity of Random Walks on Random DFA. - Borja Balle (CoRR, 2013)

Learning probabilistic automata: A study in state distinguishability. - Borja Balle; Jorge Castro; Ricard Gavaldà (Theor. Comput. Sci., 2013)

Learning finite-state machines: statistical and algorithmic aspects. - Borja Balle (2013)

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison. - Borja Balle; William L. Hamilton; Joelle Pineau (ICML, 2014)

Spectral Regularization for Max-Margin Sequence Tagging. - Ariadna Quattoni; Borja Balle; Xavier Carreras; Amir Globerson (ICML, 2014)

Adaptively learning probabilistic deterministic automata from data streams. - Borja Balle; Jorge Castro; Ricard Gavaldà (Mach. Learn., 2014)

Spectral learning of weighted automata - A forward-backward perspective. - Borja Balle; Xavier Carreras; Franco M. Luque; Ariadna Quattoni (Mach. Learn., 2014)

On the Rademacher Complexity of Weighted Automata. - Borja Balle; Mehryar Mohri (ALT, 2015)

Learning Weighted Automata. - Borja Balle; Mehryar Mohri (CAI, 2015)

A Canonical Form for Weighted Automata and Applications to Approximate Minimization. - Borja Balle; Prakash Panangaden; Doina Precup (LICS, 2015)

Learning and Planning with Timing Information in Markov Decision Processes. - Pierre-Luc Bacon; Borja Balle; Doina Precup (UAI, 2015)

Weighted Tree Automata Approximation by Singular Value Truncation. - Guillaume Rabusseau; Borja Balle; Shay B. Cohen (CoRR, 2015)

Multitask Generalized Eigenvalue Program. - Boyu Wang 002; Joelle Pineau; Borja Balle (AAAI, 2016)

Low-Rank Approximation of Weighted Tree Automata. - Guillaume Rabusseau; Borja Balle; Shay B. Cohen (AISTATS, 2016)

Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence. - Borja Balle; Rémi Eyraud; Franco M. Luque; Ariadna Quattoni; Sicco Verwer (ICGI, 2016)

Differentially Private Policy Evaluation. - Borja Balle; Maziar Gomrokchi; Doina Precup (ICML, 2016)

Learning time series models for pedestrian motion prediction. - Chenghui Zhou; Borja Balle; Joelle Pineau (ICRA, 2016)

Learning Multi-Step Predictive State Representations. - Lucas Langer; Borja Balle; Doina Precup (IJCAI, 2016)

Generalization Bounds for Weighted Automata. - Borja Balle; Mehryar Mohri (CoRR, 2016)

Secure Linear Regression on Vertically Partitioned Datasets. - Adrià Gascón; Phillipp Schoppmann; Borja Balle; Mariana Raykova 001; Jack Doerner; Samee Zahur; David Evans 001 (IACR Cryptol. ePrint Arch., 2016)

Bisimulation Metrics for Weighted Automata. - Borja Balle; Pascale Gourdeau; Prakash Panangaden (ICALP, 2017)

Spectral Learning from a Single Trajectory under Finite-State Policies. - Borja Balle; Odalric-Ambrym Maillard (ICML, 2017)

Multitask Spectral Learning of Weighted Automata. - Guillaume Rabusseau; Borja Balle; Joelle Pineau (NIPS, 2017)

Hierarchical Methods of Moments. - Matteo Ruffini; Guillaume Rabusseau; Borja Balle (NIPS, 2017)

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data. - Adrià Gascón; Phillipp Schoppmann; Borja Balle; Mariana Raykova 001; Jack Doerner; Samee Zahur; David Evans 001 (Proc. Priv. Enhancing Technol., 2017)

Learning Predictive State Representations From Non-Uniform Sampling. - Yuri Grinberg; Hossein Aboutalebi; Melanie Lyman-Abramovitch; Borja Balle; Doina Precup (AAAI, 2018)

Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising. - Borja Balle; Yu-Xiang Wang 003 (ICML, 2018)

Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences. - Borja Balle; Gilles Barthe; Marco Gaboardi (NeurIPS, 2018)

Private Nearest Neighbors Classification in Federated Databases. - Phillipp Schoppmann; Adrià Gascón; Borja Balle (IACR Cryptol. ePrint Arch., 2018)

Generalization bounds for learning weighted automata. - Borja Balle; Mehryar Mohri (Theor. Comput. Sci., 2018)

PPML '19: Privacy Preserving Machine Learning. - Borja Balle; Adrià Gascón; Olya Ohrimenko; Mariana Raykova 001; Phillipp Schoppmann; Carmela Troncoso (CCS, 2019)

The Privacy Blanket of the Shuffle Model. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CRYPTO (2), 2019)

Privacy Amplification by Mixing and Diffusion Mechanisms. - Borja Balle; Gilles Barthe; Marco Gaboardi; Joseph Geumlek (NeurIPS, 2019)

Continual Learning in Practice. - Tom Diethe; Tom Borchert; Eno Thereska; Borja Balle; Neil Lawrence (CoRR, 2019)

Privacy-preserving Active Learning on Sensitive Data for User Intent Classification. - Oluwaseyi Feyisetan; Thomas Drake; Borja Balle; Tom Diethe (CoRR, 2019)

Differentially Private Summation with Multi-Message Shuffling. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CoRR, 2019)

Improved Summation from Shuffling. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CoRR, 2019)

Actor Critic with Differentially Private Critic. - Jonathan Lebensold; William L. Hamilton; Borja Balle; Doina Precup (CoRR, 2019)

Singular value automata and approximate minimization. - Borja Balle; Prakash Panangaden; Doina Precup (Math. Struct. Comput. Sci., 2019)

Hypothesis Testing Interpretations and Renyi Differential Privacy. - Borja Balle; Gilles Barthe; Marco Gaboardi; Justin Hsu; Tetsuya Sato 001 (AISTATS, 2020)

Local Differential Privacy for Sampling. - Hisham Husain; Borja Balle; Zac Cranko; Richard Nock (AISTATS, 2020)

Model-Agnostic Counterfactual Explanations for Consequential Decisions. - Amir-Hossein Karimi; Gilles Barthe; Borja Balle; Isabel Valera (AISTATS, 2020)

Private Summation in the Multi-Message Shuffle Model. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CCS, 2020)

A Framework for robustness Certification of Smoothed Classifiers using F-Divergences. - Krishnamurthy (Dj) Dvijotham; Jamie Hayes; Borja Balle; J. Zico Kolter; Chongli Qin; András György 001; Kai Xiao; Sven Gowal; Pushmeet Kohli (ICLR, 2020)

Private Reinforcement Learning with PAC and Regret Guarantees. - Giuseppe Vietri; Borja Balle; Akshay Krishnamurthy; Zhiwei Steven Wu (ICML, 2020)

Privacy Amplification via Random Check-Ins. - Borja Balle; Peter Kairouz; Brendan McMahan; Om Dipakbhai Thakkar; Abhradeep Thakurta (NeurIPS, 2020)

Privacy-Preserving Textual Analysis via Calibrated Perturbations. - Oluwaseyi Feyisetan; Borja Balle (PrivateNLP@WSDM, 2020)

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. - Oluwaseyi Feyisetan; Borja Balle; Thomas Drake; Tom Diethe (WSDM, 2020)

Calibrating Mechanisms for Privacy Preserving Text Analysis. - Oluwaseyi Feyisetan; Borja Balle; Tom Diethe; Thomas Drake (PrivateNLP@WSDM, 2020)

Diameter and Stationary Distribution of Random $r$-Out Digraphs. - Louigi Addario-Berry; Borja Balle; Guillem Perarnau (Electron. J. Comb., 2020)

Privacy Profiles and Amplification by Subsampling. - Borja Balle; Gilles Barthe; Marco Gaboardi (J. Priv. Confidentiality, 2020)

Subsampled Rényi Differential Privacy and Analytical Moments Accountant. - Yu-Xiang Wang 003; Borja Balle; Shiva Prasad Kasiviswanathan (J. Priv. Confidentiality, 2020)

Automatic Discovery of Privacy-Utility Pareto Fronts. - Brendan Avent; Javier González 002; Tom Diethe; Andrei Paleyes; Borja Balle (Proc. Priv. Enhancing Technol., 2020)

Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue. - Phillipp Schoppmann; Lennart Vogelsang; Adrià Gascón; Borja Balle (Proc. Priv. Enhancing Technol., 2020)

Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. - Borja Balle; Clara Lacroce; Prakash Panangaden; Doina Precup; Guillaume Rabusseau (ICALP, 2021)

Ethical and social risks of harm from Language Models. - 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; et al. (CoRR, 2021)

Taxonomy of Risks posed by Language Models. - 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; et al. (FAccT, 2022)

Reconstructing Training Data with Informed Adversaries. - Borja Balle; Giovanni Cherubin; Jamie Hayes (SP, 2022)

Learning to be adversarially robust and differentially private. - Jamie Hayes; Borja Balle; M. Pawan Kumar (CoRR, 2022)

Unlocking High-Accuracy Differentially Private Image Classification through Scale. - Soham De; Leonard Berrada; Jamie Hayes; Samuel L. Smith; Borja Balle (CoRR, 2022)

Bisimulation metrics and norms for real-weighted automata. - Borja Balle; Pascale Gourdeau; Prakash Panangaden (Inf. Comput., 2022)

Approximate minimization of weighted tree automata. - Borja Balle; Guillaume Rabusseau (Inf. Comput., 2022)

Amplification by Shuffling without Shuffling. - Borja Balle; James Bell 001; Adrià Gascón (CCS, 2023)

Bounding training data reconstruction in DP-SGD. - Jamie Hayes; Borja Balle; Saeed Mahloujifar (NeurIPS, 2023)

Mnemonist: Locating Model Parameters that Memorize Training Examples. - Ali Shahin Shamsabadi; Jamie Hayes; Borja Balle; Adrian Weller (UAI, 2023)

Extracting Training Data from Diffusion Models. - Nicholas Carlini; Jamie Hayes; Milad Nasr; Matthew Jagielski; Vikash Sehwag; Florian Tramèr; Borja Balle; Daphne Ippolito; Eric Wallace (USENIX Security Symposium, 2023)

Tight Auditing of Differentially Private Machine Learning. - Milad Nasr; Jamie Hayes; Thomas Steinke 002; Borja Balle; Florian Tramèr; Matthew Jagielski; Nicholas Carlini; Andreas Terzis (USENIX Security Symposium, 2023)

UN Handbook on Privacy-Preserving Computation Techniques. - 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 001; Andrew Trask; et al. (CoRR, 2023)

Differentially Private Diffusion Models Generate Useful Synthetic Images. - Sahra Ghalebikesabi; Leonard Berrada; Sven Gowal; Ira Ktena; Robert Stanforth; Jamie Hayes; Soham De; Samuel L. Smith; Olivia Wiles; Borja Balle (CoRR, 2023)

Unlocking Accuracy and Fairness in Differentially Private Image Classification. - Leonard Berrada; Soham De; Judy Hanwen Shen; Jamie Hayes; Robert Stanforth; David Stutz; Pushmeet Kohli; Samuel L. Smith; Borja Balle (CoRR, 2023)

On the Privacy of Selection Mechanisms with Gaussian Noise. - Jonathan Lebensold; Doina Precup; Borja Balle (AISTATS, 2024)

AirGapAgent: Protecting Privacy-Conscious Conversational Agents. - Eugene Bagdasarian; Ren Yi; Sahra Ghalebikesabi; Peter Kairouz; Marco Gruteser; Sewoong Oh; Borja Balle; Daniel Ramage (CCS, 2024)

Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. - Georgios Kaissis; Stefan Kolek; Borja Balle; Jamie Hayes; Daniel Rueckert (ICML, 2024)

The Ethics of Advanced AI Assistants. - 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; et al. (CoRR, 2024)

Air Gap: Protecting Privacy-Conscious Conversational Agents. - Eugene Bagdasaryan; Ren Yi; Sahra Ghalebikesabi; Peter Kairouz; Marco Gruteser; Sewoong Oh; Borja Balle; Daniel Ramage (CoRR, 2024)

Operationalizing Contextual Integrity in Privacy-Conscious Assistants. - Sahra Ghalebikesabi; Eugene Bagdasaryan; Ren Yi; Itay Yona; Ilia Shumailov; Aneesh Pappu; Chongyang Shi 003; Laura Weidinger; Robert Stanforth; Leonard Berrada; Pushmeet Kohli; Po-Sen Huang; et al. (CoRR, 2024)

CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Data. - Zhao Cheng; Diane Wan; Matthew Abueg; Sahra Ghalebikesabi; Ren Yi; Eugene Bagdasarian; Borja Balle; Stefan Mellem; Shawn O'Banion (CoRR, 2024)

To Shuffle or not to Shuffle: Auditing DP-SGD with Shuffling. - Meenatchi Sundaram Muthu Selva Annamalai; Borja Balle; Emiliano De Cristofaro; Jamie Hayes (CoRR, 2024)

Preserving Expert-Level Privacy in Offline Reinforcement Learning. - Navodita Sharma; Vishnu Vinod; Abhradeep Thakurta; Alekh Agarwal; Borja Balle; Christoph Dann; Aravindan Raghuveer (CoRR, 2024)

Hash-Prune-Invert: Improved Differentially Private Heavy-Hitter Detection in the Two-Server Model. - Borja Balle; James Bell 001; Albert Cheu; Adrià Gascón; Jonathan Katz; Mariana Raykova 001; Phillipp Schoppmann; Thomas Steinke 002 (IACR Cryptol. ePrint Arch., 2024)

Optimal approximate minimization of one-letter weighted finite automata. - Clara Lacroce; Borja Balle; Prakash Panangaden; Guillaume Rabusseau (Math. Struct. Comput. Sci., 2024)

Scalable watermarking for identifying large language model outputs. - 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; et al. (Nat., 2024)

DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. - Xinwei Zhang 001; Zhiqi Bu; Borja Balle; Mingyi Hong 001; Meisam Razaviyayn; Vahab Mirrokni (ICLR, 2025)

The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. - Milad Nasr; Thomas Steinke 002; Borja Balle; Christopher A. Choquette-Choo; Arun Ganesh; Matthew Jagielski; Jamie Hayes; Abhradeep Guha Thakurta; Adam Smith 006; Andreas Terzis (ICLR, 2025)

Privacy Awareness for Information-Sharing Assistants: A Case-study on Form-filling with Contextual Integrity. - Sahra Ghalebikesabi; Eugene Bagdasarian; Ren Yi; Itay Yona; Ilia Shumailov; Aneesh Pappu; Chongyang Shi 003; Laura Weidinger; Robert Stanforth; Leonard Berrada; Pushmeet Kohli; Po-Sen Huang; et al. (Trans. Mach. Learn. Res., 2025)

Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography. - Ilia Shumailov; Daniel Ramage; Sarah Meiklejohn; Peter Kairouz; Florian Hartmann; Borja Balle; Eugene Bagdasarian (CoRR, 2025)

Scaling Laws for Differentially Private Language Models. - Ryan McKenna; Yangsibo Huang; Amer Sinha; Borja Balle; Zachary Charles; Christopher A. Choquette-Choo; Badih Ghazi; Georgios Kaissis; Ravi Kumar 001; Ruibo Liu; Da Yu; Chiyuan Zhang (CoRR, 2025)

(ϵ, δ) Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees. - Juan Felipe Gómez; Bogdan Kulynych; Georgios Kaissis; Jamie Hayes; Borja Balle; Antti Honkela (CoRR, 2025)

The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing. - Meenatchi Sundaram Muthu Selva Annamalai; Borja Balle; Jamie Hayes; Georgios Kaissis; Emiliano De Cristofaro (CoRR, 2025)

Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy. - Bogdan Kulynych; Juan Felipe Gómez; Georgios Kaissis; Jamie Hayes; Borja Balle; Flávio P. Calmon; Jean Louis Raisaro (CoRR, 2025)

Beyond the Worst Case: Extending Differential Privacy Guarantees to Realistic Adversaries. - Marika Swanberg; Meenatchi Sundaram Muthu Selva Annamalai; Jamie Hayes; Borja Balle; Adam D. Smith 001 (CoRR, 2025)