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KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 4 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
KDD
2009
ACM
179views Data Mining» more  KDD 2009»
14 years 4 months ago
Identifying graphs from noisy and incomplete data
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
Galileo Mark S. Namata Jr., Lise Getoor
INFOCOM
2009
IEEE
14 years 4 months ago
An Economically-Principled Generative Model of AS Graph Connectivity
We explore the problem of modeling Internet connectivity at the Autonomous System (AS) level and present an economically-principled dynamic model that reproduces key features of t...
Jacomo Corbo, Shaili Jain, Michael Mitzenmacher, D...
IROS
2009
IEEE
132views Robotics» more  IROS 2009»
14 years 4 months ago
Automatic selection of task spaces for imitation learning
Abstract— Previous work [1] shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imit...
Manuel Mühlig, Michael Gienger, Jochen J. Ste...
GECCO
2009
Springer
14 years 4 months ago
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change
In this paper, we rigorously analyse how the magnitude and frequency of change may affect the performance of the algorithm (1+1) EAdyn on a set of artificially designed pseudo-Bo...
Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao