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» Neural Learning from Unbalanced Data Using Noise Modeling
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MIR
2006
ACM
200views Multimedia» more  MIR 2006»
14 years 2 months ago
An adaptive graph model for automatic image annotation
Automatic keyword annotation is a promising solution to enable more effective image search by using keywords. In this paper, we propose a novel automatic image annotation method b...
Jing Liu, Mingjing Li, Wei-Ying Ma, Qingshan Liu, ...
WEBI
2010
Springer
13 years 6 months ago
Learning in Presence of Ontology Mapping Errors
The widespread use of ontologies to associate semantics with data has resulted in a growing interest in the problem of learning predictive models from data sources that use differe...
Neeraj Koul, Vasant Honavar
ICML
2005
IEEE
14 years 9 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
VEE
2012
ACM
322views Virtualization» more  VEE 2012»
12 years 4 months ago
Modeling virtualized applications using machine learning techniques
With the growing adoption of virtualized datacenters and cloud hosting services, the allocation and sizing of resources such as CPU, memory, and I/O bandwidth for virtual machines...
Sajib Kundu, Raju Rangaswami, Ajay Gulati, Ming Zh...
KDD
1997
ACM
109views Data Mining» more  KDD 1997»
14 years 28 days ago
Beyond Concise and Colorful: Learning Intelligible Rules
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...