| 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 | 74 | 2019 |
| 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 | 49 | 2020 |
| 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 | 22 | 2020 |
| Approximations of Geometrically Ergodic Reversible Markov Chains J Negrea, JS Rosenthal Advances in Applied Probability 53 (4), 2021 | 13* | 2021 |
| Relaxing the IID Assumption: Adaptively Minimax Optimal Regret via Root-Entropic Regularization B Bilodeau, J Negrea, DM Roy arXiv preprint arXiv:2007.06552, 2020 | 3* | 2020 |
| 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 | 2 | 2021 |
| Optimal Scaling and Shaping of Random Walk Metropolis via Diffusion Limits of Block-IID Targets J Negrea arXiv preprint arXiv:1902.06603, 2019 | 1 | 2019 |
| Approximations and scaling limits of Markov chains with applications to MCMC and approximate inference J Negrea University of Toronto, 2022 | | 2022 |
| STATISTICAL INFERENCE WITH STOCHASTIC GRADIENT ALGORITHMS J Negrea, J Yang, H Feng, DM Roy, JH Huggins | | |
