Multi-valued neurons are the neural processing elements with complex-valued weights, huge functionality (it is possible to implement on the single neuron arbitrary mapping describ...
Igor N. Aizenberg, Naum N. Aizenberg, Constantine ...
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
We develop and analyze an algorithm for nonparametric estimation of divergence functionals and the density ratio of two probability distributions. Our method is based on a variati...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...