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» Learning Models for Multi-Source Integration
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ICML
2009
IEEE
16 years 17 days ago
Learning from measurements in exponential families
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
Percy Liang, Michael I. Jordan, Dan Klein
ICASSP
2009
IEEE
15 years 3 months ago
Improved lattice-based spoken document retrieval by directly learning from the evaluation measures
Lattice-based approaches have been widely used in spoken document retrieval to handle the speech recognition uncertainty and errors. Position Specific Posterior Lattices (PSPL) an...
Chao-hong Meng, Hung-yi Lee, Lin-shan Lee
CVPR
2007
IEEE
16 years 1 months ago
Unsupervised Segmentation of Objects using Efficient Learning
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
FGR
2000
IEEE
147views Biometrics» more  FGR 2000»
15 years 4 months ago
Hallucinating Faces
In this paper, we study face hallucination or synthesizing a high-resolution face image from a low-resolution input, with the help of a large collection of other highresolution fa...
Simon Baker, Takeo Kanade
ICML
2007
IEEE
16 years 17 days ago
Comparisons of sequence labeling algorithms and extensions
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...
Nam Nguyen, Yunsong Guo