We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the a...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
We present a method for evolving and implementing artificial neural networks (ANNs) on Field Programmable Analog Arrays (FPAAs). These FPAAs offer the small size and low power usa...
Delivering continuous services in information infrastructures is a major challenge. For system or network administrators, redundancy allocation is one of the best strategies to en...
Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from se...
Heni Ben Amor, Shuhei Ikemoto, Takashi Minato, Ber...