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131
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ML
2002
ACM
128views Machine Learning» more  ML 2002»
15 years 3 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
117
Voted
ICTAI
2009
IEEE
15 years 10 months ago
EBLearn: Open-Source Energy-Based Learning in C++
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
Pierre Sermanet, Koray Kavukcuoglu, Yann LeCun
164
Voted
AAAI
2012
13 years 6 months ago
Ontological Smoothing for Relation Extraction with Minimal Supervision
Relation extraction, the process of converting natural language text into structured knowledge, is increasingly important. Most successful techniques use supervised machine learni...
Congle Zhang, Raphael Hoffmann, Daniel S. Weld
SAC
2005
ACM
15 years 9 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
164
Voted
ICML
2000
IEEE
15 years 8 months ago
Using Learning by Discovery to Segment Remotely Sensed Images
In this paper, we describe our research in computer-aided image analysis. We have incorporated machine learning methodologies with traditional image processing to perform unsuperv...
Leen-Kiat Soh, Costas Tsatsoulis