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ILP
2007
Springer
15 years 10 months ago
Bias/Variance Analysis for Relational Domains
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
ESA
2006
Springer
118views Algorithms» more  ESA 2006»
15 years 8 months ago
Subspace Sampling and Relative-Error Matrix Approximation: Column-Row-Based Methods
Much recent work in the theoretical computer science, linear algebra, and machine learning has considered matrix decompositions of the following form: given an m
Petros Drineas, Michael W. Mahoney, S. Muthukrishn...
130
Voted
JCP
2008
121views more  JCP 2008»
15 years 4 months ago
Relation Organization of SOM Initial Map by Improved Node Exchange
The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...
Tsutomu Miyoshi
ML
2010
ACM
141views Machine Learning» more  ML 2010»
15 years 2 months ago
Relational retrieval using a combination of path-constrained random walks
Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval o...
Ni Lao, William W. Cohen
ACL
2007
15 years 5 months ago
Detecting Semantic Relations between Named Entities in Text Using Contextual Features
This paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities, which may be located in different sentences. The method ...
Toru Hirano, Yoshihiro Matsuo, Gen-ichiro Kikui