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CVPR
2011
IEEE
13 years 3 months ago
Learning the Easy Things First: Self-Paced Visual Category Discovery
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
Yong Jae Lee, Kristen Grauman
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 10 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
ICPR
2008
IEEE
14 years 1 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
TSE
1998
116views more  TSE 1998»
13 years 7 months ago
A Framework-Based Approach to the Development of Network-Aware Applications
— Modern networks provide a QoS (quality of service) model to go beyond best-effort services, but current QoS models are oriented towards low-level network parameters (e.g., band...
Jürg Bolliger, Thomas R. Gross
KDD
2007
ACM
211views Data Mining» more  KDD 2007»
14 years 8 months ago
Enhanced max margin learning on multimodal data mining in a multimedia database
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...