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ICML
2000
IEEE
14 years 8 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
EVOW
2008
Springer
13 years 9 months ago
Composing Music with Neural Networks and Probabilistic Finite-State Machines
In this paper, biological (human) music composition systems based on Time Delay Neural Networks and Ward Nets and on a probabilistic Finite-State Machine will be presented. The sys...
Tomasz Michal Oliwa, Markus Wagner
ICML
2005
IEEE
14 years 8 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert
CVPR
2010
IEEE
13 years 5 months ago
Growing semantically meaningful models for visual SLAM
Though modern Visual Simultaneous Localisation and Mapping (vSLAM) systems are capable of localising robustly and efficiently even in the case of a monocular camera, the maps prod...
Alexander Flint, Christopher Mei, Ian D. Reid, Dav...
COLT
2004
Springer
14 years 1 months ago
Replacing Limit Learners with Equally Powerful One-Shot Query Learners
Different formal learning models address different aspects of human learning. Below we compare Gold-style learning—interpreting learning as a limiting process in which the lear...
Steffen Lange, Sandra Zilles