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CVPR
2008
IEEE
14 years 10 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
ECCV
2004
Springer
14 years 10 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
DAWAK
2000
Springer
14 years 1 months ago
COFE: A Scalable Method for Feature Extraction from Complex Objects
Abstract. Feature Extraction, also known as Multidimensional Scaling, is a basic primitive associated with indexing, clustering, nearest neighbor searching and visualization. We co...
Gabriela Hristescu, Martin Farach-Colton
NIPS
2004
13 years 10 months ago
Variational Minimax Estimation of Discrete Distributions under KL Loss
We develop a family of upper and lower bounds on the worst-case expected KL loss for estimating a discrete distribution on a finite number m of points, given N i.i.d. samples. Our...
Liam Paninski
JCT
2011
115views more  JCT 2011»
13 years 3 months ago
Sharp thresholds for hypergraph regressive Ramsey numbers
The f-regressive Ramsey number Rreg f (d, n) is the minimum N such that every colouring of the d-tuples of an N-element set mapping each x1, . . . , xd to a colour ≤ f(x1) contai...
Lorenzo Carlucci, Gyesik Lee, Andreas Weiermann