NONPARAMETRIC DECOMPOSITION OF SPARSE TENSORS

von TILLINGHAST, CONOR
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 13 of 16 (2022)

Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition

von Wang, Zheng
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 28 of 33 (2023)

Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes

von Tillinghast, Conor
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 26 of 33 (2023)

STREAMING NONLINEAR BAYESIAN TENSOR DECOMPOSITION

von PAN, ZHIMENG
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (36. : 2020 : Online) 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020) ; Volume 2 of 3 (2021)

Rapid Seismic Risk Assessment of Structures with Gaussian Process Regression

von Sheibani, Mohamadreza
Veröffentlicht in IMAC (37. : 2019 : Orlando, Fla.) Proceedings of the 37th IMAC, a Conference and Exposition on Structural Dynamics 2019 ; Volume 4: Dynamic substructures (2020)

SELF-MODULATING NONPARAMETRIC EVENT-TENSOR FACTORIZATION

von Wang, Zheng
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 13 of 15 (2021)

Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks

von Li, Shibo
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 30 of 36 (2022)

BAYESIAN STREAMING SPARSE TUCKER DECOMPOSITION

von Fang, Shikai
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (37. : 2021 : Online) 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) ; Part 1 of 3 (2022)

The Combinatorial Brain Surgeon: Pruning Weights that Cancel One Another in Neural Networks

von Yu, Xin
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 31 of 33 (2023)

Infinite-Fidelity Coregionalization for Physical Simulation

von Li, Shibo
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 34 of 50 (2023)

Bayesian Continuous-Time Tucker Decomposition

von Fang, Shikai
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 8 of 33 (2023)

Multi-Fidelity Bayesian Optimization via Deep Neural Networks

von Li, Shibo
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 11 of 27 (2021)

Self-Adaptable Point Processes with Nonparametric Time Decays

von Pan, Zhimeng
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 6 of 36 (2022)

STREAMING BAYESIAN DEEP TENSOR FACTORIZATION

von FANG, SHIKAI
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 4 of 16 (2022)

Characterizing possible failure modes in physics-informed neural networks

von Krishnapriyan, Aditi
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 32 of 36 (2022)

Batch Multi-Fidelity Active Learning with Budget Constraints

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

Nonparametric Embeddings of Sparse High-Order Interaction Events

von Wang, Zheng
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 28 of 33 (2023)

AutoIP: A United Framework to Integrate Physics into Gaussian Processes

von Long, Da
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 17 of 33 (2023)

Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm

von Good, Aidan
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 42 of 50 (2023)

Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions

von Cai, Junyang
Veröffentlicht in CPAIOR (20. : 2023 : Nizza) Integration of constraint programming, artificial intelligence, and operations research (2023)