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AAAI
2007
15 years 9 months ago
Multi-Label Learning by Instance Differentiation
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
Min-Ling Zhang, Zhi-Hua Zhou
NIPS
2008
15 years 8 months ago
Regularized Learning with Networks of Features
For many supervised learning problems, we possess prior knowledge about which features yield similar information about the target variable. In predicting the topic of a document, ...
Ted Sandler, John Blitzer, Partha Pratim Talukdar,...
IJCAI
2003
15 years 8 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
NIPS
1998
15 years 8 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
CSL
2007
Springer
15 years 6 months ago
Speaker-adaptive learning of resonance targets in a hidden trajectory model of speech coarticulation
A novel speaker-adaptive learning algorithm is developed and evaluated for a hidden trajectory model of speech coarticulation and reduction. Central to this model is the process o...
Dong Yu, Li Deng, Alex Acero