Rademacher, Luis

11 publications

NeurIPS 2024 Euclidean Distance Compression via Deep Random Features Brett Leroux, Luis Rademacher

AISTATS 2024 On the Nyström Approximation for Preconditioning in Kernel Machines Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher, Mikhail Belkin

AAAI 2017 Heavy-Tailed Analogues of the Covariance Matrix for ICA Joseph Anderson, Navin Goyal, Anupama Nandi, Luis Rademacher

COLT 2016 Basis Learning as an Algorithmic Primitive Mikhail Belkin, Luis Rademacher, James R. Voss

AAAI 2016 The Hidden Convexity of Spectral Clustering James R. Voss, Mikhail Belkin, Luis Rademacher

NeurIPS 2015 A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA James R Voss, Mikhail Belkin, Luis Rademacher

COLT 2014 The More, the Merrier: The Blessing of Dimensionality for Learning Large Gaussian Mixtures Joseph Anderson, Mikhail Belkin, Navin Goyal, Luis Rademacher, James R. Voss

COLT 2013 Blind Signal Separation in the Presence of Gaussian Noise Mikhail Belkin, Luis Rademacher, James R. Voss

COLT 2013 Efficient Learning of Simplices Joseph Anderson, Navin Goyal, Luis Rademacher

NeurIPS 2013 Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis James R Voss, Luis Rademacher, Mikhail Belkin

COLT 2009 Learning Convex Bodies Is Hard Luis Rademacher, Navin Goyal