Nystrom Approximation for Large-Scale Determinantal Processes

Determinantal point processes (DPPs) are appealing models for subset selection problems where diversity is desired. They oer surprisingly ecient inference, including sam

[1]  E. Candès,et al.  Sparsity and incoherence in compressive sampling , 2006, math/0611957.

[2]  Alan M. Frieze,et al.  Fast Monte-Carlo algorithms for finding low-rank approximations , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[3]  Matthias W. Seeger,et al.  Using the Nyström Method to Speed Up Kernel Machines , 2000, NIPS.

[4]  Santosh S. Vempala,et al.  Matrix approximation and projective clustering via volume sampling , 2006, SODA '06.

[5]  Rong Jin,et al.  Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison , 2012, NIPS.

[6]  Ben Taskar,et al.  Structured Determinantal Point Processes , 2010, NIPS.

[7]  Ben Taskar,et al.  k-DPPs: Fixed-Size Determinantal Point Processes , 2011, ICML.

[8]  Alan M. Frieze,et al.  Fast monte-carlo algorithms for finding low-rank approximations , 2004, JACM.

[9]  Ameet Talwalkar,et al.  Sampling Methods for the Nyström Method , 2012, J. Mach. Learn. Res..

[10]  E. Rains,et al.  Eynard–Mehta Theorem, Schur Process, and their Pfaffian Analogs , 2004, math-ph/0409059.

[11]  Petros Drineas,et al.  On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning , 2005, J. Mach. Learn. Res..

[12]  Ben Taskar,et al.  Discovering Diverse and Salient Threads in Document Collections , 2012, EMNLP.

[13]  Y. Peres,et al.  Determinantal Processes and Independence , 2005, math/0503110.

[14]  Ameet Talwalkar,et al.  Matrix Coherence and the Nystrom Method , 2010, UAI.

[15]  Nicholas Arcolano,et al.  Approximation of Positive Semidefinite Matrices Using the Nystrom Method , 2011 .