← Authors

Borja Balle

28 papers · 2012–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (13) 🌟 Keyword Trendsetter Combo (3) πŸ”¬ Deep Specialist (12) πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter πŸ’Ž Century Club (28) πŸ—ƒοΈ Keyword Collector (85) ⚑ Prolific Year (6) πŸ”₯ Unstoppable (5)

Conferences

ICML (8) NIPS (7) AISTATS (6) ICLR (3) EACL (1) EMNLP (1) IJCAI (1) UAI (1)

Top co-authors

Jamie Hayes (5) Gilles Barthe (4) Ariadna Quattoni (3) Guillaume Rabusseau (3) Xavier Carreras (3) Doina Precup (3) Marco Gaboardi (3) Abhradeep Guha Thakurta (2) Yu-Xiang Wang (2) Georgios Kaissis (2)

Research topics

Differential Privacy (2) Privacy (2)

Keywords

differential privacy (8) spectral learning (3) weighted automaton (3) privacy amplification (3) hankel matrix (3) spectral method (3) privacy-preserving machine learning (2) gaussian mechanism (2) privacy accounting (2) latent variable model (2) singular value decomposition (2) weighted automata (2) expectation maximization (1) topic modeling (1) reinforcement learning (1) density estimation (1) decision making (1) privacy attack (1) federated learning (1) structured prediction (1)

Papers

DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction ICLR 2025
Scaling Laws for Differentially Private Language Models ICML 2025
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD ICLR 2025
On the Privacy of Selection Mechanisms with Gaussian Noise AISTATS 2024
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy ICML 2024
Mnemonist: Locating Model Parameters that Memorize Training Examples UAI 2023
Bounding training data reconstruction in DP-SGD NIPS 2023
Private Reinforcement Learning with PAC and Regret Guarantees ICML 2020
Privacy Amplification via Random Check-Ins NIPS 2020
Model-Agnostic Counterfactual Explanations for Consequential Decisions AISTATS 2020
Hypothesis Testing Interpretations and Renyi Differential Privacy AISTATS 2020
Local Differential Privacy for Sampling AISTATS 2020
A FRAMEWORK FOR ROBUSTNESS CERTIFICATION OF SMOOTHED CLASSIFIERS USING F-DIVERGENCES ICLR 2020
Subsampled Renyi Differential Privacy and Analytical Moments Accountant AISTATS 2019
Privacy Amplification by Mixing and Diffusion Mechanisms NIPS 2019
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences NIPS 2018
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising ICML 2018
Hierarchical Methods of Moments NIPS 2017
Multitask Spectral Learning of Weighted Automata NIPS 2017
Spectral Learning from a Single Trajectory under Finite-State Policies ICML 2017
Differentially Private Policy Evaluation ICML 2016
Low-Rank Approximation of Weighted Tree Automata AISTATS 2016
Learning Multi-Step Predictive State Representations IJCAI 2016
Spectral Learning Techniques for Weighted Automata, Transducers, and Grammars EMNLP 2014
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison ICML 2014
Spectral Regularization for Max-Margin Sequence Tagging ICML 2014
Spectral Learning of General Weighted Automata via Constrained Matrix Completion NIPS 2012
Spectral Learning for Non-Deterministic Dependency Parsing EACL 2012