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» RANSAC-SVM for large-scale datasets
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ICCS
2004
Springer
14 years 2 months ago
Chunking-Coordinated-Synthetic Approaches to Large-Scale Kernel Machines
We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
Francisco J. González-Castaño, Rober...
HIPC
2000
Springer
14 years 22 days ago
Meta-data Management System for High-Performance Large-Scale Scientific Data Access
Many scientific applications manipulate large amount of data and, therefore, are parallelized on high-performance computing systems to take advantage of their computational power a...
Wei-keng Liao, Xiaohui Shen, Alok N. Choudhary
AAIM
2008
Springer
208views Algorithms» more  AAIM 2008»
13 years 11 months ago
Large-Scale Parallel Collaborative Filtering for the Netflix Prize
Many recommendation systems suggest items to users by utilizing the techniques of collaborative filtering (CF) based on historical records of items that the users have viewed, purc...
Yunhong Zhou, Dennis M. Wilkinson, Robert Schreibe...
ML
2010
ACM
124views Machine Learning» more  ML 2010»
13 years 7 months ago
Large scale image annotation: learning to rank with joint word-image embeddings
Image annotation datasets are becoming larger and larger, with tens of millions of images and tens of thousands of possible annotations. We propose a strongly performing method tha...
Jason Weston, Samy Bengio, Nicolas Usunier
ICCV
2011
IEEE
12 years 9 months ago
Generalized Subgraph Preconditioners for Large-Scale Bundle Adjustment
We present a generalized subgraph preconditioning (GSP) technique to solve large-scale bundle adjustment problems efficiently. In contrast with previous work which uses either di...
Yong-Dian Jian, Doru C. Balcan, Frank Dellaert