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AAAI
1997
15 years 7 months ago
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
Tom Bylander
SODA
1998
ACM
114views Algorithms» more  SODA 1998»
15 years 7 months ago
Exact Arithmetic at Low Cost - A Case Study in Linear Programming
We describe a new exact-arithmetic approach to linear programming when the number of variables n is much larger than the number of constraints m (or vice versa). The algorithm is ...
Bernd Gärtner
AMC
2006
75views more  AMC 2006»
15 years 6 months ago
Common stabilizers for linear control systems in the presence of actuators outage
This paper presents common stabilizers for linear control systems when actuators happen to fail. The possible outage of actuators examined in this study are not confined to a pre-s...
Yew-Wen Liang, Der-Cherng Liaw
AUTOMATICA
2006
120views more  AUTOMATICA 2006»
15 years 6 months ago
Transition probability bounds for the stochastic stability robustness of continuous- and discrete-time Markovian jump linear sys
This paper considers the robustness of stochastic stability of Markovian jump linear systems in continuous- and discrete-time with respect to their transition rates and probabilit...
Mehmet Karan, Peng Shi, C. Yalçin Kaya
IJON
2008
177views more  IJON 2008»
15 years 6 months ago
An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem
In this paper, an approach to solving the classical Traveling Salesman Problem (TSP) using a recurrent network of linear threshold (LT) neurons is proposed. It maps the classical ...
Eu Jin Teoh, Kay Chen Tan, H. J. Tang, Cheng Xiang...