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CVPR
2007
IEEE
16 years 8 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
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...
Fabien Scalzo, Justus H. Piater
ICML
2005
IEEE
16 years 7 months ago
Fast inference and learning in large-state-space HMMs
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...
Sajid M. Siddiqi, Andrew W. Moore
ICASSP
2009
IEEE
16 years 1 months ago
Connecting spectral and spring methods for manifold learning
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
Shannon M. Hughes, Peter J. Ramadge
IROS
2006
IEEE
168views Robotics» more  IROS 2006»
16 years 26 days ago
Learning to Drive Among Obstacles
— 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...
Bradley Hamner, Sebastian Scherer, Sanjiv Singh
SYNASC
2005
IEEE
97views Algorithms» more  SYNASC 2005»
16 years 12 days ago
A Reinforcement Learning Algorithm for Spiking Neural Networks
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 ...
Razvan V. Florian