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» An Efficient Algorithm for Local Distance Metric Learning
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UAI
2000
15 years 1 months ago
The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data
This paper is about the use of metric data structures in high-dimensionalor non-Euclidean space to permit cached sufficientstatisticsaccelerationsof learning algorithms. It has re...
Andrew W. Moore
ACL
2008
15 years 1 months ago
Analyzing the Errors of Unsupervised Learning
We identify four types of errors that unsupervised induction systems make and study each one in turn. Our contributions include (1) using a meta-model to analyze the incorrect bia...
Percy Liang, Dan Klein
ML
2006
ACM
142views Machine Learning» more  ML 2006»
14 years 11 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
ICML
2009
IEEE
16 years 20 days ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
GIS
2002
ACM
14 years 11 months ago
A road network embedding technique for k-nearest neighbor search in moving object databases
A very important class of queries in GIS applications is the class of K-Nearest Neighbor queries. Most of the current studies on the K-Nearest Neighbor queries utilize spatial ind...
Cyrus Shahabi, Mohammad R. Kolahdouzan, Mehdi Shar...