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» A Framework for Multiple-Instance Learning
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CISST
2004
164views Hardware» more  CISST 2004»
15 years 5 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
IJCAI
2003
15 years 5 months ago
Active Learning with Strong and Weak Views: A Case Study on Wrapper Induction
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
Ion Muslea, Steven Minton, Craig A. Knoblock
NIPS
2003
15 years 5 months ago
Perspectives on Sparse Bayesian Learning
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
David P. Wipf, Jason A. Palmer, Bhaskar D. Rao
AAAI
1997
15 years 5 months ago
Benefits of Learning in Negotiation
Negotiation has been extensively discussed in gametheoretic, economic, and management science literatures for decades. Recent growing interest in electronic commerce has given inc...
Dajun Zeng, Katia P. Sycara
AAAI
1996
15 years 5 months ago
Formalizing Dependency Directed Backtracking and Explanation Based Learning in Refinement Search
The ideas of dependency directed backtracking (DDB) and explanation based learning (EBL) have developed independently in constraint satisfaction, planning and problem solving comm...
Subbarao Kambhampati