We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
For Hidden Markov Models (HMMs) with fully connected transition models, the three fundamental problems of evaluating the likelihood of an observation sequence, estimating an optim...
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
— This paper reports on an outdoor mobile robot that learns to avoid collisions by observing a human driver operate a vehicle equipped with sensors that continuously produce a ma...
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...