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CVPR
2005
IEEE
16 years 8 months ago
A Bayesian Hierarchical Model for Learning Natural Scene Categories
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
PCI
2005
Springer
16 years 7 days ago
Gossip-Based Greedy Gaussian Mixture Learning
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
ICPR
2002
IEEE
15 years 11 months ago
Hierarchical Interpretation of Human Activities Using Competitive Learning
In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learni...
Harry Wechsler, Zoran Duric, Fayin Li
FLAIRS
2008
15 years 9 months ago
The Introspective Robot: Using Self-Prediction to Improve Robot Learning
We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...
NIPS
2007
15 years 8 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh