Representing Hyperbolic Space Accurately using Multi-Component Floats

von Yu, Tao
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 19 of 36 (2022)

GraB: Finding Provably Better Data Permutations than Random Reshuffling

von Lu, Yucheng
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 12 of 50 (2023)

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning

von Yu, Tao
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 2 of 50 (2023)

Hyperparameter Optimization Is Deceiving Us, and How to Stop It

von Cooper, A. Feder
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 4 of 36 (2022)

Model Preserving Compression for Neural Networks

von Chee, Jerry
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 49 of 50 (2023)

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent

von De Sa, Christopher M
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 40 of 50 (2023)

Equivariant Manifold Flows

von Katsman, Isay
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 13 of 36 (2022)