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Jeffrey Negrea
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Information-theoretic generalization bounds for SGLD via data-dependent estimates
J Negrea, M Haghifam, GK Dziugaite, A Khisti, DM Roy
Advances in Neural Information Processing Systems 32, 2019
1382019
Sharpened generalization bounds based on conditional mutual information and an application to noisy, iterative algorithms
M Haghifam, J Negrea, A Khisti, DM Roy, GK Dziugaite
Advances in Neural Information Processing Systems 33, 2020
1012020
In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors
J Negrea, GK Dziugaite, D Roy
Proceedings of the 37th International Conference on Machine Learning, 2020
542020
Concept Algebra for (Score-Based) Text-Controlled Generative Models
Z Wang, L Gui, J Negrea, V Veitch
Advances in Neural Information Processing Systems 36, 2024
21*2024
Approximations of Geometrically Ergodic Reversible Markov Chains
J Negrea, JS Rosenthal
Advances in Applied Probability 53 (4), 2021
18*2021
Relaxing the iid assumption: Adaptively minimax optimal regret via root-entropic regularization
B Bilodeau, J Negrea, DM Roy
The Annals of Statistics 51 (4), 1850-1876, 2023
102023
Minimax optimal quantile and semi-adversarial regret via root-logarithmic regularizers
J Negrea, B Bilodeau, N Campolongo, F Orabona, D Roy
Advances in Neural Information Processing Systems 34, 26237-26249, 2021
52021
Optimal Scaling and Shaping of Random Walk Metropolis via Diffusion Limits of Block-IID Targets
J Negrea
arXiv preprint arXiv:1902.06603, 2019
22019
STATISTICAL INFERENCE WITH STOCHASTIC GRADIENT ALGORITHMS
J Negrea, J Yang, H Feng, DM Roy, JH Huggins
2*
Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics
J Negrea, J Yang, H Feng, DM Roy, JH Huggins
arXiv preprint arXiv:2207.12395, 2022
2022
Approximations and Scaling Limits of Markov Chains with Applications to MCMC and Approximate Inference
J Negrea
2022
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Articles 1–11