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» Choosing Multiple Parameters for Support Vector Machines
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TKDE
2010
182views more  TKDE 2010»
13 years 6 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
TNN
2008
178views more  TNN 2008»
13 years 7 months 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
JUCS
2008
136views more  JUCS 2008»
13 years 7 months ago
Crime Scene Representation (2D, 3D, Stereoscopic Projection) and Classification
: In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be u...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...
JMLR
2012
11 years 10 months ago
Maximum Margin Temporal Clustering
Temporal Clustering (TC) refers to the factorization of multiple time series into a set of non-overlapping segments that belong to k temporal clusters. Existing methods based on e...
Minh Hoai Nguyen, Fernando De la Torre
ICSE
2001
IEEE-ACM
14 years 10 days ago
A Framework for Multi-Valued Reasoning over Inconsistent Viewpoints
In requirements elicitation, different stakeholders often hold different views of how a proposed system should behave, resulting in inconsistencies between their descriptions. Con...
Steve M. Easterbrook, Marsha Chechik