James R. Voss

13 papers A* 4Journal 7Unranked 2
YearRankTypeTitle / Venue / Authors
2018 J jnl
Eigenvectors of Orthogonally Decomposable Functions.
SIAM J. Comput.
Mikhail Belkin, Luis Rademacher, James R. Voss
2016 A* conf
Basis Learning as an Algorithmic Primitive.
COLT
Mikhail Belkin, Luis Rademacher, James R. Voss
2016 A* conf
The Hidden Convexity of Spectral Clustering.
AAAI
James R. Voss, Mikhail Belkin, Luis Rademacher
2015 — conf
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA.
NIPS
James R. Voss, Mikhail Belkin, Luis Rademacher
2015 J jnl
Optimal Recovery in Noisy ICA.
CoRR
James R. Voss, Mikhail Belkin, Luis Rademacher
2014 J jnl
Learning a Hidden Basis Through Imperfect Measurements: An Algorithmic Primitive.
CoRR
Mikhail Belkin, Luis Rademacher, James R. Voss
2014 J jnl
Matching preclusion and conditional matching preclusion for pancake and burnt pancake graphs.
Int. J. Parallel Emergent Distributed Syst.
Eddie Cheng, Philip Hu, Roger Jia, László Lipták, Brian Scholten, James R. Voss
2014 J jnl
The Hidden Convexity of Spectral Clustering.
CoRR
Mikhail Belkin, Luis Rademacher, James R. Voss
2014 A* conf
The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures.
COLT
Joseph Anderson, Mikhail Belkin, Navin Goyal, Luis Rademacher, James R. Voss
2013 A* conf
Blind Signal Separation in the Presence of Gaussian Noise.
COLT
Mikhail Belkin, Luis Rademacher, James R. Voss
2013 — conf
Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis.
NIPS
James R. Voss, Luis Rademacher, Mikhail Belkin
2013 J jnl
The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures.
CoRR
Joseph Anderson, Mikhail Belkin, Navin Goyal, Luis Rademacher, James R. Voss
2012 J jnl
Blind Signal Separation in the Presence of Gaussian Noise
CoRR
Mikhail Belkin, Luis Rademacher, James R. Voss