Algorithmic Stability for Adaptive Data Analysis

8 November 2015

Papers citing "Algorithmic Stability for Adaptive Data Analysis"

50 / 75 papers shown

Title
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 62 1 0 08 Nov 2023
Adversarially Robust Distributed Count Tracking via Partial Differential Privacy Zhongzheng Xiong Xiaoyi Zhu Zengfeng Huang 25 1 0 01 Nov 2023
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks Jiayuan Ye Zhenyu Zhu Fanghui Liu Reza Shokri V. Cevher 42 12 0 31 Oct 2023
Generalization Guarantees via Algorithm-dependent Rademacher Complexity Sarah Sachs T. Erven Liam Hodgkinson Rajiv Khanna Umut Simsekli 25 3 0 04 Jul 2023
Adaptive Data Analysis in a Balanced Adversarial Model Kobbi Nissim Uri Stemmer Eliad Tsfadia FedML 20 1 0 24 May 2023
Statistical Indistinguishability of Learning Algorithms Alkis Kalavasis Amin Karbasi Shay Moran Grigoris Velegkas 25 16 0 23 May 2023
How Spurious Features Are Memorized: Precise Analysis for Random and NTK Features Simone Bombari Marco Mondelli AAML 44 5 0 20 May 2023
List and Certificate Complexities in Replicable Learning P. Dixon A. Pavan Jason Vander Woude N. V. Vinodchandran 35 12 0 05 Apr 2023
Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization Mark Bun Marco Gaboardi Max Hopkins R. Impagliazzo Rex Lei T. Pitassi Satchit Sivakumar Jessica Sorrell 28 29 0 22 Mar 2023
PRIMO: Private Regression in Multiple Outcomes Seth Neel 25 0 0 07 Mar 2023
On Differential Privacy and Adaptive Data Analysis with Bounded Space Itai Dinur Uri Stemmer David P. Woodruff Samson Zhou 29 12 0 11 Feb 2023
Generalized Private Selection and Testing with High Confidence E. Cohen Xin Lyu Jelani Nelson Tamas Sarlos Uri Stemmer 20 6 0 22 Nov 2022
Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang Yunwen Lei Yiming Ying Ding-Xuan Zhou 24 18 0 16 Sep 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 69 6 0 08 Sep 2022
Valid Inference after Causal Discovery Paula Gradu Tijana Zrnic Yixin Wang Michael I. Jordan CML 28 8 0 11 Aug 2022
Improved Generalization Guarantees in Restricted Data Models Elbert Du Cynthia Dwork 25 1 0 20 Jul 2022
On the Privacy Properties of GAN-generated Samples Zinan Lin Vyas Sekar Giulia Fanti PICV 24 26 0 03 Jun 2022
Making Progress Based on False Discoveries Roi Livni 38 0 0 19 Apr 2022
Low-Degree Multicalibration Parikshit Gopalan Michael P. Kim M. Singhal Shengjia Zhao FaML UQCV 22 37 0 02 Mar 2022
Causal Imitation Learning under Temporally Correlated Noise Gokul Swamy Sanjiban Choudhury J. Andrew Bagnell Zhiwei Steven Wu CML 24 29 0 02 Feb 2022
Reproducibility in Learning R. Impagliazzo Rex Lei T. Pitassi Jessica Sorrell 32 43 0 20 Jan 2022
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 34 14 0 22 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 135 120 0 07 Oct 2021
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators Idan Attias E. Cohen M. Shechner Uri Stemmer 26 29 0 30 Jul 2021
Adaptive Machine Unlearning Varun Gupta Christopher Jung Seth Neel Aaron Roth Saeed Sharifi-Malvajerdi Chris Waites MU 25 174 0 08 Jun 2021
Non-Euclidean Differentially Private Stochastic Convex Optimization: Optimal Rates in Linear Time Raef Bassily Cristóbal Guzmán Anupama Nandi 59 66 0 01 Mar 2021
Machine Unlearning via Algorithmic Stability Enayat Ullah Tung Mai Anup B. Rao Ryan Rossi R. Arora 35 103 0 25 Feb 2021
Estimating informativeness of samples with Smooth Unique Information Hrayr Harutyunyan Alessandro Achille Giovanni Paolini Orchid Majumder Avinash Ravichandran Rahul Bhotika Stefano Soatto 27 25 0 17 Jan 2021
A bounded-noise mechanism for differential privacy Y. Dagan Gil Kur 25 22 0 07 Dec 2020
Outcome Indistinguishability Cynthia Dwork Michael P. Kim Omer Reingold G. Rothblum G. Yona 22 61 0 26 Nov 2020
Transfer Meta-Learning: Information-Theoretic Bounds and Information Meta-Risk Minimization Sharu Theresa Jose Osvaldo Simeone G. Durisi 31 17 0 04 Nov 2020
Permute-and-Flip: A new mechanism for differentially private selection Ryan McKenna Daniel Sheldon 112 47 0 23 Oct 2020
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification Yingxue Zhou Zhiwei Steven Wu A. Banerjee 29 108 0 07 Jul 2020
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds Yingxue Zhou Xiangyi Chen Mingyi Hong Zhiwei Steven Wu A. Banerjee 24 25 0 24 Jun 2020
Information-Theoretic Generalization Bounds for Meta-Learning and Applications Sharu Theresa Jose Osvaldo Simeone 38 45 0 09 May 2020
Efficient, Noise-Tolerant, and Private Learning via Boosting Mark Bun M. Carmosino Jessica Sorrell FedML 21 17 0 04 Feb 2020
Reasoning About Generalization via Conditional Mutual Information Thomas Steinke Lydia Zakynthinou 23 160 0 24 Jan 2020
The power of synergy in differential privacy: Combining a small curator with local randomizers A. Beimel Aleksandra Korolova Kobbi Nissim Or Sheffet Uri Stemmer 34 14 0 18 Dec 2019
A New Analysis of Differential Privacy's Generalization Guarantees Christopher Jung Katrina Ligett Seth Neel Aaron Roth Saeed Sharifi-Malvajerdi Moshe Shenfeld FedML 21 47 0 09 Sep 2019
Private Stochastic Convex Optimization with Optimal Rates Raef Bassily Vitaly Feldman Kunal Talwar Abhradeep Thakurta 23 237 0 27 Aug 2019
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions Matthew Faw Rajat Sen Karthikeyan Shanmugam Constantine Caramanis Sanjay Shakkottai 36 3 0 23 Jul 2019
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis Ryan M. Rogers Aaron Roth Adam D. Smith Nathan Srebro Om Thakkar Blake E. Woodworth 16 17 0 21 Jun 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 38 122 0 04 Jun 2019
Model Similarity Mitigates Test Set Overuse Horia Mania John Miller Ludwig Schmidt Moritz Hardt Benjamin Recht 22 50 0 29 May 2019
Private Identity Testing for High-Dimensional Distributions C. Canonne Gautam Kamath Audra McMillan Jonathan R. Ullman Lydia Zakynthinou 37 36 0 28 May 2019
The advantages of multiple classes for reducing overfitting from test set reuse Vitaly Feldman Roy Frostig Moritz Hardt 29 29 0 24 May 2019
Towards Formalizing the GDPR's Notion of Singling Out A. Cohen Kobbi Nissim 21 82 0 12 Apr 2019
A New Approach to Adaptive Data Analysis and Learning via Maximal Leakage A. Esposito Michael C. Gastpar Ibrahim Issa 11 7 0 05 Mar 2019
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate Vitaly Feldman J. Vondrák 35 154 0 27 Feb 2019
The Optimal Approximation Factor in Density Estimation Olivier Bousquet D. Kane Shay Moran 19 18 0 10 Feb 2019