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Composable Core-sets for Determinant Maximization Problems via Spectral
  Spanners
v1v2 (latest)

Composable Core-sets for Determinant Maximization Problems via Spectral Spanners

31 July 2018
Piotr Indyk
S. Mahabadi
S. Gharan
A. Rezaei
ArXiv (abs)PDFHTML

Papers citing "Composable Core-sets for Determinant Maximization Problems via Spectral Spanners"

13 / 13 papers shown
Title
Proportional Volume Sampling and Approximation Algorithms for A-Optimal
  Design
Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design
Aleksandar Nikolov
Mohit Singh
U. Tantipongpipat
67
48
0
22 Feb 2018
Near-Optimal Discrete Optimization for Experimental Design: A Regret
  Minimization Approach
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach
Zeyuan Allen-Zhu
Yuanzhi Li
Aarti Singh
Yining Wang
68
59
0
14 Nov 2017
Subdeterminant Maximization via Nonconvex Relaxations and
  Anti-concentration
Subdeterminant Maximization via Nonconvex Relaxations and Anti-concentration
J. Ebrahimi
D. Straszak
Nisheeth K. Vishnoi
54
12
0
10 Jul 2017
Following the Leader and Fast Rates in Linear Prediction: Curved
  Constraint Sets and Other Regularities
Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities
Ruitong Huang
Tor Lattimore
András Gyorgy
Csaba Szepesvári
52
31
0
10 Feb 2017
MapReduce and Streaming Algorithms for Diversity Maximization in Metric
  Spaces of Bounded Doubling Dimension
MapReduce and Streaming Algorithms for Diversity Maximization in Metric Spaces of Bounded Doubling Dimension
Matteo Ceccarello
A. Pietracaprina
G. Pucci
E. Upfal
47
34
0
18 May 2016
Randomized Composable Core-sets for Distributed Submodular Maximization
Randomized Composable Core-sets for Distributed Submodular Maximization
Vahab Mirrokni
Morteza Zadimoghaddam
154
128
0
22 Jun 2015
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Kamalika Chaudhuri
Sham Kakade
Praneeth Netrapalli
Sujay Sanghavi
68
72
0
08 Jun 2015
The Power of Randomization: Distributed Submodular Maximization on
  Massive Datasets
The Power of Randomization: Distributed Submodular Maximization on Massive Datasets
R. Barbosa
Alina Ene
Huy Le Nguyen
Justin Ward
193
103
0
09 Feb 2015
Large-Margin Determinantal Point Processes
Large-Margin Determinantal Point Processes
Boqing Gong
Wei-lun Chao
Kristen Grauman
Fei Sha
77
50
0
06 Nov 2014
Distributed Submodular Maximization
Distributed Submodular Maximization
Baharan Mirzasoleiman
Amin Karbasi
Rik Sarkar
Andreas Krause
98
206
0
03 Nov 2014
Linear Bandits in High Dimension and Recommendation Systems
Linear Bandits in High Dimension and Recommendation Systems
Y. Deshpande
Andrea Montanari
OffRL
141
71
0
08 Jan 2013
Determinantal point processes for machine learning
Determinantal point processes for machine learning
Alex Kulesza
B. Taskar
274
1,140
0
25 Jul 2012
Learning Determinantal Point Processes
Learning Determinantal Point Processes
Alex Kulesza
B. Taskar
89
162
0
14 Feb 2012
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