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IJCV
2010
152views more  IJCV 2010»
13 years 6 months ago
Learning Articulated Structure and Motion
Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to learn the st...
David A. Ross, Daniel Tarlow, Richard S. Zemel
NIPS
2008
13 years 9 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey
CORR
2010
Springer
96views Education» more  CORR 2010»
13 years 7 months ago
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
KDD
2008
ACM
121views Data Mining» more  KDD 2008»
14 years 8 months ago
Reconstructing chemical reaction networks: data mining meets system identification
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Yong Ju Cho, Naren Ramakrishnan, Yang Cao
ICCV
2005
IEEE
14 years 1 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...