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2004
Springer
14 years 3 months ago
The Correspondence Problem in Topological Metric Mapping - Using Absolute Metric Maps to Close Cycles
In Simultaneous Localisation and Mapping (SLAM) the correspondence problem, specifically detecting cycles, is one of the most difficult challenges for an autonomous mobile robot. ...
Margaret E. Jefferies, Michael C. Cosgrove, Jesse ...
STOC
2004
ACM
126views Algorithms» more  STOC 2004»
14 years 10 months ago
Bypassing the embedding: algorithms for low dimensional metrics
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...
Kunal Talwar

Publication
417views
14 years 6 months ago
Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces
We consider the computational problem of finding nearest neighbors in general metric spaces. Of particular interest are spaces that may not be conveniently embedded or approximate...
Peter N. Yianilos
ICPR
2008
IEEE
14 years 4 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
SODA
2008
ACM
125views Algorithms» more  SODA 2008»
13 years 11 months ago
Ultra-low-dimensional embeddings for doubling metrics
We consider the problem of embedding a metric into low-dimensional Euclidean space. The classical theorems of Bourgain, and of Johnson and Lindenstrauss say that any metric on n p...
T.-H. Hubert Chan, Anupam Gupta, Kunal Talwar