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Determinantal Point Processes in Randomized Numerical Linear Algebra

Determinantal Point Processes in Randomized Numerical Linear Algebra

7 May 2020
Michal Derezinski
Michael W. Mahoney
ArXivPDFHTML

Papers citing "Determinantal Point Processes in Randomized Numerical Linear Algebra"

14 / 14 papers shown
Title
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
Sangwoo Shin
H. Hino
19
0
0
02 Aug 2024
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems
Younghyun Cho
James Demmel
Michal Derezinski
Haoyun Li
Hengrui Luo
Michael W. Mahoney
Riley Murray
27
5
0
30 Aug 2023
Sharp Analysis of Sketch-and-Project Methods via a Connection to
  Randomized Singular Value Decomposition
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition
Michal Derezinski
E. Rebrova
22
16
0
20 Aug 2022
Neurotoxin: Durable Backdoors in Federated Learning
Neurotoxin: Durable Backdoors in Federated Learning
Zhengming Zhang
Ashwinee Panda
Linyue Song
Yaoqing Yang
Michael W. Mahoney
Joseph E. Gonzalez
Kannan Ramchandran
Prateek Mittal
FedML
17
129
0
12 Jun 2022
Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches
Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches
Michal Derezinski
42
5
0
06 Jun 2022
Optimal Sublinear Sampling of Spanning Trees and Determinantal Point
  Processes via Average-Case Entropic Independence
Optimal Sublinear Sampling of Spanning Trees and Determinantal Point Processes via Average-Case Entropic Independence
Nima Anari
Yang P. Liu
T. Vuong
21
15
0
06 Apr 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
D. Long
Z. Wang
Aditi S. Krishnapriyan
Robert M. Kirby
Shandian Zhe
Michael W. Mahoney
AI4CE
19
14
0
24 Feb 2022
L1 Regression with Lewis Weights Subsampling
L1 Regression with Lewis Weights Subsampling
Aditya Parulekar
Advait Parulekar
Eric Price
17
19
0
19 May 2021
Sparse sketches with small inversion bias
Sparse sketches with small inversion bias
Michal Derezinski
Zhenyu Liao
Edgar Dobriban
Michael W. Mahoney
15
21
0
21 Nov 2020
Testing Determinantal Point Processes
Testing Determinantal Point Processes
Khashayar Gatmiry
Maryam Aliakbarpour
Stefanie Jegelka
19
1
0
09 Aug 2020
Sampling from a $k$-DPP without looking at all items
Sampling from a kkk-DPP without looking at all items
Daniele Calandriello
Michal Derezinski
Michal Valko
19
22
0
30 Jun 2020
Precise expressions for random projections: Low-rank approximation and
  randomized Newton
Precise expressions for random projections: Low-rank approximation and randomized Newton
Michal Derezinski
Feynman T. Liang
Zhenyu A. Liao
Michael W. Mahoney
19
23
0
18 Jun 2020
Reverse iterative volume sampling for linear regression
Reverse iterative volume sampling for linear regression
Michal Derezinski
Manfred K. Warmuth
39
43
0
06 Jun 2018
Determinantal point processes for machine learning
Determinantal point processes for machine learning
Alex Kulesza
B. Taskar
162
1,122
0
25 Jul 2012
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