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» Learning Hierarchical Shape Models from Examples
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ICTAI
2007
IEEE
14 years 4 months ago
ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming
In this paper we developed an Inductive Logic Programming (ILP) based framework ExOpaque that is able to extract a set of Horn clauses from an arbitrary opaque machine learning mo...
Yunsong Guo, Bart Selman
NIPS
2004
13 years 11 months ago
Learning first-order Markov models for control
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
Pieter Abbeel, Andrew Y. Ng
CHI
2005
ACM
14 years 10 months ago
Supporting efficient development of cognitive models at multiple skill levels: exploring recent advances in constraint-based mod
This paper presents X-PRT, a new cognitive modeling tool supporting activities ranging from interface design to basic cognitive research. X-PRT provides a graphical model developm...
Irene Tollinger, Richard L. Lewis, Michael McCurdy...
BMCBI
2011
13 years 1 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
VISUALIZATION
1997
IEEE
14 years 2 months ago
Dynamic smooth subdivision surfaces for data visualization
Recursive subdivision schemes have been extensively used in computer graphics and scientific visualization for modeling smooth surfaces of arbitrary topology. Recursive subdivisi...
Chhandomay Mandal, Hong Qin, Baba C. Vemuri