conftrace_

differential privacy

1,207 papers

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Also known as

DP

Co-occurring keywords · papers mentioning both

federated learning (146) stochastic gradient descent (72) sample complexity (68) regret bound (53) privacy-preserving learning (49) privacy preservation (47) privacy-preserving machine learning (43) privacy-utility trade-off (42) synthetic data (37) large language model (36)

Papers

On Convex Optimization with Semi-Sensitive Features COLT 2024 On Differentially Private Federated Linear Contextual Bandits ICLR 2024 On Differentially Private Subspace Estimation in a Distribution-Free Setting NeurIPS 2024 On Differentially Private U Statistics NeurIPS 2024 One-shot Empirical Privacy Estimation for Federated Learning ICLR 2024 Online Sensitivity Optimization in Differentially Private Learning AAAI 2024 On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint) IJCAI 2024 On provable privacy vulnerabilities of graph representations NeurIPS 2024 On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift NeurIPS 2024 On the Computational Complexity of Private High-dimensional Model Selection NeurIPS 2024 On the Computational Landscape of Replicable Learning NeurIPS 2024 On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective COLT 2024 On the Privacy of Selection Mechanisms with Gaussian Noise AISTATS 2024 On the sample complexity of privately learning half-spaces ACML 2024 Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives NeurIPS 2024 Open Problem: Optimal Rates for Stochastic Decision-Theoretic Online Learning Under Differentially Privacy COLT 2024 Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits? COLT 2024 Optimal Differentially Private Model Training with Public Data ICML 2024 Optimal Learning Policies for Differential Privacy in Multi-armed Bandits JMLR 2024 Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime NeurIPS 2024 Optimizing Noise for f-Differential Privacy via Anti-Concentration and Stochastic Dominance JMLR 2024 Oracle-Efficient Differentially Private Learning with Public Data NeurIPS 2024 Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding AAAI 2024 Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining ICML 2024 Pre-training Differentially Private Models with Limited Public Data NeurIPS 2024