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MP
2008
101views more  MP 2008»
15 years 4 months ago
Accelerating the cubic regularization of Newton's method on convex problems
In this paper we propose an accelerated version of the cubic regularization of Newton's method [6]. The original version, used for minimizing a convex function with Lipschitz...
Yu. Nesterov
SIAMJO
2008
104views more  SIAMJO 2008»
15 years 4 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd
AUTOMATICA
2005
112views more  AUTOMATICA 2005»
15 years 4 months ago
Optimal controller tuning for nonlinear processes
: This work proposes a systematic methodology for the optimal selection of controller parameters, in the sense of minimizing a performance index which is a quadratic function of th...
Nikolaos Kazantzis, Costas Kravaris, Costas Tseron...
TSP
2008
97views more  TSP 2008»
15 years 3 months ago
Risk-Sensitive Particle Filters for Mitigating Sample Impoverishment
Risk-sensitive filters (RSF) put a penalty to higher-order moments of the estimation error compared to conventional filters as the Kalman filter minimizing the mean square error. ...
Umut Orguner, Fredrik Gustafsson
144
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TC
2002
15 years 3 months ago
A Deterministic Multivariate Interpolation Algorithm for Small Finite Fields
We present a new multivariate interpolation algorithm over arbitrary fields which is primarily suited for small finite fields. Given function values at arbitrary t points, we show ...
Zeljko Zilic, Zvonko G. Vranesic