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» On an Optimization Problem in Sensor Selection*
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ECML
2007
Springer
15 years 4 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
GLOBECOM
2007
IEEE
15 years 4 months ago
Improving Connectivity via Relays Deployment in Wireless Sensor Networks
Abstract— Enhancing the connectivity of wireless sensor networks is necessary to avoid the occurrence of coverage gaps. In this paper, we aim at improving the network connectivit...
Ahmed S. Ibrahim, Karim G. Seddik, K. J. Ray Liu
CAV
2003
Springer
140views Hardware» more  CAV 2003»
15 years 3 months ago
Certifying Optimality of State Estimation Programs
Abstract. The theme of this paper is certifying software for state estimation of dynamic systems, which is an important problem found in spacecraft, aircraft, geophysical, and in m...
Grigore Rosu, Ram Prasad Venkatesan, Jon Whittle, ...
MOBIWAC
2006
ACM
15 years 4 months ago
Quick convergecast in ZigBee/IEEE 802.15.4 tree-based wireless sensor networks
Convergecast is a fundamental operation in wireless sensor networks. Existing convergecast solutions have focused on reducing latency and energy consumption. However, a good desig...
Yu-Chee Tseng, Meng-Shiuan Pan
JMLR
2012
13 years 16 days ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu