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109
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ICANN
2003
Springer
15 years 8 months ago
A Comparison of Model Aggregation Methods for Regression
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
Zafer Barutçuoglu
150
Voted
ICML
2007
IEEE
16 years 4 months ago
Learning from interpretations: a rooted kernel for ordered hypergraphs
The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
Gabriel Wachman, Roni Khardon
123
Voted
ICML
2005
IEEE
16 years 4 months ago
Preference learning with Gaussian processes
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Wei Chu, Zoubin Ghahramani
131
Voted
MLDM
2005
Springer
15 years 9 months ago
Diagnosis of Lung Nodule Using Reinforcement Learning and Geometric Measures
This paper uses a set of 3D geometric measures with the purpose of characterizing lung nodules as malignant or benign. Based on a sample of 36 nodules, 29 benign and 7 malignant, t...
Aristófanes Corrêa Silva, Valdeci Rib...
119
Voted
ICMLA
2008
15 years 5 months ago
Image Segmentation as Learning on Hypergraphs
In this paper, we propose to use hypergraphs as the model for images and pose image segmentation as a machine learning problem in which some pixels (called seeds) are labeled as t...
Lei Ding, Alper Yilmaz