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Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data.

, , , , , , and . KDD, page 3011-3021. ACM, (2023)

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The Interpolating Information Criterion for Overparameterized Models., , , , and . CoRR, (2023)Compressing Deep ODE-Nets using Basis Function Expansions., , , and . CoRR, (2021)Generalization Properties of Stochastic Optimizers via Trajectory Analysis., , , and . CoRR, (2021)Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 8774-8795. PMLR, (2022)Multiplicative Noise and Heavy Tails in Stochastic Optimization., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 4262-4274. PMLR, (2021)Implicit Langevin Algorithms for Sampling From Log-concave Densities., , and . J. Mach. Learn. Res., (2021)Stochastic continuous normalizing flows: training SDEs as ODEs., , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1130-1140. AUAI Press, (2021)A PAC-Bayesian Perspective on the Interpolating Information Criterion., , , , and . CoRR, (2023)Stochastic Normalizing Flows., , , and . CoRR, (2020)Noisy Recurrent Neural Networks., , , and . NeurIPS, page 5124-5137. (2021)