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» Regularization Methods for Additive Models
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NIPS
2007
15 years 1 months ago
Bundle Methods for Machine Learning
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
MICCAI
2003
Springer
16 years 16 days ago
Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution
3D freehand ultrasound imaging is becoming a widespread technique in medical examinations. This imaging technique produces a set of irregularly spaced B-scans. Reconstructing a reg...
Raúl San José Estépar, Marcos...
STOC
2010
ACM
220views Algorithms» more  STOC 2010»
15 years 3 months ago
Combinatorial approach to the interpolation method and scaling limits in sparse random graphs
We establish the existence of free energy limits for several sparse random hypergraph models corresponding to certain combinatorial models on Erd¨os-R´enyi graph G(N, c/N) and r...
Mohsen Bayati, David Gamarnik, Prasad Tetali
NIPS
2008
15 years 1 months ago
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung
91
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ICCV
2007
IEEE
16 years 1 months ago
A Globally Optimal Algorithm for Robust TV-L1 Range Image Integration
Robust integration of range images is an important task for building high-quality 3D models. Since range images, and in particular range maps from stereo vision, may have a substa...
Christopher Zach, Thomas Pock, Horst Bischof