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HIS
2008
13 years 7 months ago
Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Salvador García, Francisco Herrera
JMLR
2012
11 years 8 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
ICCV
2005
IEEE
13 years 11 months ago
LOCUS: Learning Object Classes with Unsupervised Segmentation
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
John M. Winn, Nebojsa Jojic
NECO
2007
150views more  NECO 2007»
13 years 5 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
SAB
2010
Springer
212views Optimization» more  SAB 2010»
13 years 3 months ago
A Study of Adaptive Locomotive Behaviors of a Biped Robot: Patterns Generation and Classification
Abstract. Neurobiological studies showed the important role of Centeral Pattern Generators for spinal cord in the control and sensory feedback of animals' locomotion. In this ...
John Nassour, Patrick Henaff, Fathi Ben Ouezdou, G...