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» Structured metric learning for high dimensional problems
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ECCV
2002
Springer
14 years 10 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal
VLDB
2002
ACM
110views Database» more  VLDB 2002»
13 years 8 months ago
Eliminating Fuzzy Duplicates in Data Warehouses
The duplicate elimination problem of detecting multiple tuples, which describe the same real world entity, is an important data cleaning problem. Previous domain independent solut...
Rohit Ananthakrishna, Surajit Chaudhuri, Venkatesh...
ICCV
2003
IEEE
14 years 11 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
SIGMOD
2010
ACM
324views Database» more  SIGMOD 2010»
14 years 1 months ago
Similarity search and locality sensitive hashing using ternary content addressable memories
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Rajendra Shinde, Ashish Goel, Pankaj Gupta, Debojy...
ICML
2006
IEEE
14 years 5 months ago
Cover Trees for Nearest Neighbor
We present a tree data structure for fast nearest neighbor operations in general n- point metric spaces (where the data set con- sists of n points). The data structure re- quir...
Alina Beygelzimer, Sham Kakade, John Langford