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125
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CVPR
2007
IEEE
15 years 4 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
129
Voted
COLING
2008
15 years 2 months ago
Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
Gholamreza Haffari, Anoop Sarkar
110
Voted
TNN
2008
178views more  TNN 2008»
15 years 19 days ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 5 months ago
Improving data mining utility with projective sampling
Overall performance of the data mining process depends not just on the value of the induced knowledge but also on various costs of the process itself such as the cost of acquiring...
Mark Last
IJCAI
2007
15 years 2 months ago
Maximum Margin Coresets for Active and Noise Tolerant Learning
We study the problem of learning large margin halfspaces in various settings using coresets to show that coresets are a widely applicable tool for large margin learning. A large m...
Sariel Har-Peled, Dan Roth, Dav Zimak