889 search results - page 26 / 178 » Observational Learning in Random Networks |
IJCAI
2001
13 years 11 months ago
2001
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
ICCV
2007
IEEE
14 years 11 months ago
2007
IEEE
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
IJCNN
2006
IEEE
14 years 3 months ago
2006
IEEE
—In Liquid State Machines, separation is a critical attribute of the liquid—which is traditionally not trained. The effects of using Hebbian learning in the liquid to improve s...
IM
2008
13 years 9 months ago
2008
In this paper we consider three models for random graphs that utilize the inner product as their fundamental object. We analyze the behavior of these models with respect to cluster...
ESANN
2007
13 years 11 months ago
2007
We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...