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» Large-Scale Many-Class Learning
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CAIP
2003
Springer
222views Image Analysis» more  CAIP 2003»
14 years 3 months ago
Learning Statistical Structure for Object Detection
Abstract. Many classes of images exhibit sparse structuring of statistical dependency. Each variable has strong statistical dependency with a small number of other variables and ne...
Henry Schneiderman
JMLR
2006
108views more  JMLR 2006»
13 years 9 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...
CVPR
2000
IEEE
14 years 12 months ago
Learning from One Example through Shared Densities on Transforms
We define a process called congealing in which elements of a dataset (images) are brought into correspondence with each other jointly, producing a data-defined model. It is based ...
Erik G. Miller, Nicholas E. Matsakis, Paul A. Viol...
CIVR
2008
Springer
222views Image Analysis» more  CIVR 2008»
13 years 11 months ago
Automatic image annotation via local multi-label classification
As the consequence of semantic gap, visual similarity does not guarantee semantic similarity, which in general is conflicting with the inherent assumption of many generativebased ...
Mei Wang, Xiangdong Zhou, Tat-Seng Chua
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 10 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...