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FOCS
2006
IEEE
15 years 9 months ago
Hardness of Learning Halfspaces with Noise
Learning an unknown halfspace (also called a perceptron) from labeled examples is one of the classic problems in machine learning. In the noise-free case, when a halfspace consist...
Venkatesan Guruswami, Prasad Raghavendra
ICCV
2011
IEEE
14 years 3 months ago
Optical Flow Estimation Using Learned Sparse Model
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
Kui Jia, Xiaogang Wang, Xiaoou Tang
JMLR
2006
131views more  JMLR 2006»
15 years 3 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser
NIPS
2003
15 years 4 months ago
Kernel Dimensionality Reduction for Supervised Learning
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
ICML
2009
IEEE
16 years 4 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos