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Determinantal Point Processes (DPPs) provide an elegant and versatile way to sample sets of items that balance the point-wise quality with the set-wise diversity of selected items.
über die praktische auflösung von integralgleichungen mit anwendungen auf randwertaufgaben
E.J. Nyström · 1930
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M.L. Mehta and M. Gaudin · 1960
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J. Ginibre · 1965
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The coincidence approach to stochastic point processes
Odile Macchi · 1975
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Comparison of three methods for selecting values of input variables in the analysis of output from a computer code
M. D. McKay, R. J. Beckman, and W. J. Conover · 1979
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The ellipsoid method and its consequences in combinatorial optimization
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Robin Pemantle · 2000
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The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, and Jerome Friedman · 2001
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Using the nyström method to speed up kernel machines
Christopher K. I. Williams and Matthias Seeger · 2001
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Determinantal processes with number variance saturation
Kurt Johansson · 2004
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Eynard–Mehta theorem, Schur process, and their Pfaffian analogs
Alexei Borodin and Eric M. Rains · 2005
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Determinantal processes and independence
J. Ben Hough, Manjunath Krishnapur, Yuval Peres, and Bálint Virág · 2006
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Applications of stable polynomials to mixed determinants: Johnson’s conjectures, unimodality, and symmetrized Fischer products
Julius Borcea and Petter Brändén · 2008
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Negative dependence and the geometry of polynomials
Julius Borcea, Petter Brändén, and Thomas M. Liggett · 2009
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Determinantal Point Processes, 2009
Alexei Borodin · 2009
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Zeros of Gaussian Analytic Functions and Determinantal Point Processes
J.B. Hough, M. Krishnapur, Y. Peres, and B. Vir´ag · 2009
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MNIST handwritten digit database
Yann LeCun and Corinna Cortes · 2010
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Solving the apparent diversity-accuracy dilemma of recommender systems
T. Zhou, Z. Kuscsik, J.G. Liu, M. Medo, J.R. Wakeling, and Y.C. Zhang · 2010
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k-DPPs: Fixed-size Determinantal Point Processes
Alex Kulesza and Ben Taskar · 2011
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A tight linear time (1/2)-approximation for unconstrained submodular maximization
Niv Buchbinder, Moran Feldman, Joseph (Seffi) Naor, and Roy Schwartz · 2012
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Large-margin Determinantal Point Processes
Wei-Lun Chao, Boqing Gong, Kristen Grauman, and Fei Sha · 2015
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The movielens datasets: History and context
F. Maxwell Harper and Joseph A. Konstan · 2015
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Submodular Point Processes with Applications to Machine learning
Rishabh Iyer and Jeffrey Bilmes · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Interlacing families II: Mixed characteristic polynomials and the Kadison–Singer problem
Adam Marcus, Daniel Spielman, and Nikhil Srivastava · 2015
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Submodularity in data subset selection and active learning
Kai Wei, Rishabh Iyer, and Jeff Bilmes · 2015
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Alex Kulesza and Ben Taskar · 2012
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Priors for diversity in generative latent variable models
James Zou and Ryan Prescott Adams · 2012
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Nystrom approximation for large-scale determinantal processes
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A Determinantal Point Process latent variable model for inhibition in neural spiking data
Jasper Snoek, Richard S. Zemel, and Ryan Prescott Adams · 2013
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Learning the parameters of Determinantal Point Process kernels
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Diverse sequential subset selection for supervised video summarization
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Low-rank factorization of Determinantal Point Processes
Mike Gartrell, Ulrich Paquet, and Noam Koenigstein · 2017
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Attention is all you need
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Stochastic learning on imbalanced data: Determinantal Point Processes for mini-batch diversification
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Fast greedy MAP inference for Determinantal Point Process to improve recommendation diversity
Laming Chen, Guoxin Zhang, and Eric Zhou · 2018
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Andrew Cotter, Maya R. Gupta, Heinrich Jiang, James Muller, Taman Narayan, Serena Wang, and Tao Zhu · 2018
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