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IDA
2007
Springer
13 years 7 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
ICRA
2007
IEEE
160views Robotics» more  ICRA 2007»
14 years 1 months ago
OOPS for Motion Planning: An Online, Open-source, Programming System
— The success of sampling-based motion planners has resulted in a plethora of methods for improving planning components, such as sampling and connection strategies, local planner...
Erion Plaku, Kostas E. Bekris, Lydia E. Kavraki
TSP
2011
161views more  TSP 2011»
13 years 2 months ago
Mean-Square Error in Periodogram Approaches With Adaptive Windowing
Abstract—Modified periodogram approaches are nonparametric power spectral density (PSD) estimators. Here, we present a method for estimating the mean-square error (MSE) of these...
Soosan Beheshti, M. Ravan, J. P. Reilly, L. J. Tra...
DATE
2010
IEEE
142views Hardware» more  DATE 2010»
13 years 7 months ago
Transition-aware real-time task scheduling for reconfigurable embedded systems
—Due to increase in demand for reconfigurability in embedded systems, real-time task scheduling is challenged by non-negligible reconfiguration overheads. If such overheads are n...
Hessam Kooti, Elaheh Bozorgzadeh, Shenghui Liao, L...
NECO
2008
108views more  NECO 2008»
13 years 7 months ago
An SMO Algorithm for the Potential Support Vector Machine
We describe a fast Sequential Minimal Optimization (SMO) procedure for solving the dual optimization problem of the recently proposed Potential Support Vector Machine (P-SVM). The...
Tilman Knebel, Sepp Hochreiter, Klaus Obermayer