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CVPR
2007
IEEE
16 years 26 days ago
Autocalibration via Rank-Constrained Estimation of the Absolute Quadric
We present an autocalibration algorithm for upgrading a projective reconstruction to a metric reconstruction by estimating the absolute dual quadric. The algorithm enforces the ra...
Manmohan Krishna Chandraker, Sameer Agarwal, Fredr...
ECCC
2002
103views more  ECCC 2002»
14 years 10 months ago
Monotone complexity and the rank of matrices
We shall give simpler proofs of some lower bounds on monotone computations. We describe a simple condition on combinatorial structures, such that the rank of the matrix associated...
Pavel Pudlák
ICML
2010
IEEE
14 years 12 months ago
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, His...
ICCAD
2001
IEEE
124views Hardware» more  ICCAD 2001»
15 years 7 months ago
Highly Accurate Fast Methods for Extraction and Sparsification of Substrate Coupling Based on Low-Rank Approximation
More aggressive design practices have created renewed interest in techniques for analyzing substrate coupling problems. Most previous work has focused primarily on faster techniqu...
Joe Kanapka, Jacob White
SIAMSC
2008
148views more  SIAMSC 2008»
14 years 10 months ago
Multilevel Adaptive Aggregation for Markov Chains, with Application to Web Ranking
A multilevel adaptive aggregation method for calculating the stationary probability vector of an irreducible stochastic matrix is described. The method is a special case of the ada...
Hans De Sterck, Thomas A. Manteuffel, Stephen F. M...