Emile Richard
Emile Richard
Verifierad e-postadress på stanford.edu - Startsida
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Estimation of simultaneously sparse and low rank matrices
E Richard, PA Savalle, N Vayatis
arXiv preprint arXiv:1206.6474, 2012
1672012
A statistical model for tensor PCA
E Richard, A Montanari
Advances in Neural Information Processing Systems 27, 2897-2905, 2014
1462014
A statistical model for tensor PCA
E Richard, A Montanari
Advances in Neural Information Processing Systems 27, 2897-2905, 2014
1462014
Content contributor management and network effects in a UGC environment
K Zhang, T Evgeniou, V Padmanabhan, E Richard
Marketing Science 31 (3), 433-447, 2012
702012
Non-negative principal component analysis: Message passing algorithms and sharp asymptotics
A Montanari, E Richard
IEEE Transactions on Information Theory 62 (3), 1458-1484, 2015
672015
Tight convex relaxations for sparse matrix factorization
E Richard, GR Obozinski, JP Vert
Advances in neural information processing systems 27, 3284-3292, 2014
482014
Link prediction in graphs with autoregressive features.
E Richard, S Gaïffas, N Vayatis
J. Mach. Learn. Res. 15 (1), 565-593, 2014
362014
Link discovery using graph feature tracking
E Richard, N Baskiotis, T Evgeniou, N Vayatis
Advances in Neural Information Processing Systems, 1966-1974, 2010
302010
Cone-constrained principal component analysis
Y Deshpande, A Montanari, E Richard
Advances in Neural Information Processing Systems 27, 2717-2725, 2014
242014
Cone-constrained principal component analysis
Y Deshpande, A Montanari, E Richard
Advances in Neural Information Processing Systems 27, 2717-2725, 2014
242014
Recognizing retinal ganglion cells in the dark
E Richard, GA Goetz, EJ Chichilnisky
Advances in Neural Information Processing Systems 28, 2476-2484, 2015
202015
Intersecting singularities for multi-structured estimation
E Richard, B Francis, JP Vert
International Conference on Machine Learning, 1157-1165, 2013
162013
Extragradient method in optimization: Convergence and complexity
TP Nguyen, E Pauwels, E Richard, BW Suter
Journal of Optimization Theory and Applications 176 (1), 137-162, 2018
152018
Link prediction in graphs with autoregressive features
E Richard, S Gaiffas, N Vayatis
Advances in neural information processing systems 25, 2834-2842, 2012
122012
Crystalline structure of accretion disks: Features of a global model
G Montani, R Benini
Physical Review E 84 (2), 026406, 2011
122011
A regularization approach for prediction of edges and node features in dynamic graphs
E Richard, A Argyriou, T Evgeniou, N Vayatis
arXiv preprint arXiv:1203.5438, 2012
12012
Regularization methods for prediction in dynamic graphs and e-marketing applications
E Richard
2012
Graph Prediction in a Low-Rank and Autoregressive Setting
E Richard, PA Savalle, N Vayatis
arXiv preprint arXiv:1205.1406, 2012
2012
Link Prediction in Graphs with Autoregressive Features
E Richard, S Gaïffas, N Vayatis
Advances in Neural Information Processing Systems 25, 2834-2842, 2012
2012
ICML 2012
E Richard, PA Savalle, N Vayatis
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Artiklar 1–20