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2006.07340
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Fourier Sparse Leverage Scores and Approximate Kernel Learning
Neural Information Processing Systems (NeurIPS), 2020
12 June 2020
T. Erdélyi
Cameron Musco
Christopher Musco
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Papers citing
"Fourier Sparse Leverage Scores and Approximate Kernel Learning"
15 / 15 papers shown
Importance Sampling for Nonlinear Models
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Fred Roosta
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0
18 May 2025
Provably Accurate Shapley Value Estimation via Leverage Score Sampling
International Conference on Learning Representations (ICLR), 2024
Christopher Musco
R. Teal Witter
FAtt
FedML
TDI
436
18
0
02 Oct 2024
Agnostic Active Learning of Single Index Models with Linear Sample Complexity
Annual Conference Computational Learning Theory (COLT), 2024
Aarshvi Gajjar
Wai Ming Tai
Xingyu Xu
Chinmay Hegde
Yi Li
Chris Musco
410
12
0
15 May 2024
A unified framework for learning with nonlinear model classes from arbitrary linear samples
International Conference on Machine Learning (ICML), 2023
Ben Adcock
Juan M. Cardenas
N. Dexter
283
5
0
25 Nov 2023
Model-adapted Fourier sampling for generative compressed sensing
Aaron Berk
Simone Brugiapaglia
Y. Plan
Matthew Scott
Xia Sheng
Özgür Yilmaz
242
4
0
08 Oct 2023
Improved Active Learning via Dependent Leverage Score Sampling
International Conference on Learning Representations (ICLR), 2023
Atsushi Shimizu
Xiaoou Cheng
Chris Musco
Jonathan Weare
FedML
449
9
0
08 Oct 2023
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions
Neural Information Processing Systems (NeurIPS), 2023
Ben Adcock
Juan M. Cardenas
N. Dexter
436
12
0
01 Jun 2023
Active Learning for Single Neuron Models with Lipschitz Non-Linearities
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Aarshvi Gajjar
Chinmay Hegde
Christopher Musco
476
13
0
24 Oct 2022
On The Relative Error of Random Fourier Features for Preserving Kernel Distance
International Conference on Learning Representations (ICLR), 2022
Kuan Cheng
S. Jiang
Luojian Wei
Zhide Wei
348
2
0
01 Oct 2022
Generalized Leverage Scores: Geometric Interpretation and Applications
International Conference on Machine Learning (ICML), 2022
Bruno Ordozgoiti
Antonis Matakos
Aristides Gionis
187
7
0
16 Jun 2022
Near Optimal Reconstruction of Spherical Harmonic Expansions
Neural Information Processing Systems (NeurIPS), 2022
A. Zandieh
Insu Han
H. Avron
238
1
0
25 Feb 2022
Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning
H. Yamasaki
Sho Sonoda
295
8
0
16 Jun 2021
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines
Fanghui Liu
Xiaolin Huang
Yudong Chen
Johan A. K. Suykens
370
4
0
03 Nov 2020
Hutch++: Optimal Stochastic Trace Estimation
SIAM Symposium on Simplicity in Algorithms (SOSA), 2020
R. A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
528
142
0
19 Oct 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond
Fanghui Liu
Xiaolin Huang
Yudong Chen
Johan A. K. Suykens
BDL
541
200
0
23 Apr 2020
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