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SPAA
2009
ACM
16 years 1 months ago
A randomized, o(log w)-depth 2 smoothing network
A K-smoothing network is a distributed, low-contention data structure where tokens arrive arbitrarily on w input wires and reach w output wires via their completely asynchronous p...
Marios Mavronicolas, Thomas Sauerwald
IJON
2007
112views more  IJON 2007»
15 years 4 months ago
Extraction of spatio-temporal primitives of emotional body expressions
Experimental and computational studies suggest that complex motor behavior is based on simpler spatiotemporal primitives, or synergies. This has been demonstrated by application o...
Lars Omlor, Martin A. Giese
CHI
2011
ACM
14 years 8 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
JMIV
2006
185views more  JMIV 2006»
15 years 4 months ago
Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements
In medical image analysis and high level computer vision, there is an intensive use of geometric features like orientations, lines, and geometric transformations ranging from simp...
Xavier Pennec
JMLR
2006
108views more  JMLR 2006»
15 years 4 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...