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» Learning Algorithms for Domain Adaptation
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FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
15 years 6 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
103
Voted
IJCAI
2003
15 years 2 months ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
101
Voted
INLG
2010
Springer
14 years 10 months ago
Named Entity Generation Using Sampling-based Structured Prediction
The problem of Named Entity Generation is expressed as a conditional probability model over a structured domain. By defining a factor-graph model over the mentions of a text, we o...
Guillaume Bouchard
106
Voted
WWW
2006
ACM
16 years 1 months ago
Beyond PageRank: machine learning for static ranking
Since the publication of Brin and Page's paper on PageRank, many in the Web community have depended on PageRank for the static (query-independent) ordering of Web pages. We s...
Matthew Richardson, Amit Prakash, Eric Brill
CVPR
2011
IEEE
14 years 4 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk