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» Learning from General Label Constraints
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KDD
2010
ACM
245views Data Mining» more  KDD 2010»
14 years 2 days ago
Flexible constrained spectral clustering
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Xiang Wang, Ian Davidson
ICCV
2011
IEEE
12 years 8 months ago
Conditional Random Fields for Multi-Camera Object Detection
We formulate a model for multi-class object detection in a multi-camera environment. From our knowledge, this is the first time that this problem is addressed taken into account ...
Xavier Boix, Gemma Roig, Horesh Ben Shitrit, Pasca...
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
14 years 16 days ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen
KCAP
2005
ACM
14 years 2 months ago
Acquisition and maintenance of constraints in engineering design
The Designers’ Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as RollsRoyce, by makin...
Suraj Ajit, Derek H. Sleeman, David W. Fowler, Dav...
CVPR
2010
IEEE
14 years 5 months ago
Optimizing One-Shot Recognition with Micro-Set Learning
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...