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» Computing Small Search Numbers in Linear Time
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FOCS
1999
IEEE
13 years 12 months ago
Learning Mixtures of Gaussians
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Sanjoy Dasgupta
ECCV
2000
Springer
14 years 5 hour ago
How Does CONDENSATION Behave with a Finite Number of Samples?
Abstract. Condensation is a popular algorithm for sequential inference that resamples a sampled representation of the posterior. The algorithm is known to be asymptotically correct...
Oliver D. King, David A. Forsyth
BMCBI
2010
150views more  BMCBI 2010»
13 years 5 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
STOC
2003
ACM
178views Algorithms» more  STOC 2003»
14 years 8 months ago
Uniform hashing in constant time and linear space
Many algorithms and data structures employing hashing have been analyzed under the uniform hashing assumption, i.e., the assumption that hash functions behave like truly random fu...
Anna Östlin, Rasmus Pagh
COMGEO
1999
ACM
13 years 7 months ago
Dynamic algorithms for geometric spanners of small diameter: Randomized solutions
Let S be a set of n points in IRd and let t > 1 be a real number. A t-spanner for S is a directed graph having the points of S as its vertices, such that for any pair p and q o...
Sunil Arya, David M. Mount, Michiel H. M. Smid