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42,936
A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm
- IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS
, 1993
"... A new learning algorithm for multilayer feedforward networks, RPROP, is proposed. To overcome the inherent disadvantages of pure gradient-descent, RPROP performs a local adaptation of the weight-updates according to the behaviour of the errorfunction. In substantial difference to other adaptive tech ..."
Abstract
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Cited by 938 (34 self)
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A new learning algorithm for multilayer feedforward networks, RPROP, is proposed. To overcome the inherent disadvantages of pure gradient-descent, RPROP performs a local adaptation of the weight-updates according to the behaviour of the errorfunction. In substantial difference to other adaptive
A Highly Adaptive Distributed Routing Algorithm for Mobile Wireless Networks
, 1997
"... We present a new distributed routing protocol for mobile, multihop, wireless networks. The protocol is one of a family of protocols which we term "link reversal" algorithms. The protocol's reaction is structured as a temporally-ordered sequence of diffusing computations; each computat ..."
Abstract
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Cited by 1100 (6 self)
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" of the distributed algorithm. This capability is unique among protocols which are stable in the face of network partitions, and results in the protocol's high degree of adaptivity. This desirable behavior is achieved through the novel use of a "physical or logical clock" to establish the "
Adaptive Constraint Satisfaction
- WORKSHOP OF THE UK PLANNING AND SCHEDULING
, 1996
"... Many different approaches have been applied to constraint satisfaction. These range from complete backtracking algorithms to sophisticated distributed configurations. However, most research effort in the field of constraint satisfaction algorithms has concentrated on the use of a single algorithm fo ..."
Abstract
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Cited by 952 (43 self)
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for solving all problems. At the same time, a consensus appears to have developed to the effect that it is unlikely that any single algorithm is always the best choice for all classes of problem. In this paper we argue that an adaptive approach should play an important part in constraint satisfaction
The algorithmic analysis of hybrid systems
- THEORETICAL COMPUTER SCIENCE
, 1995
"... We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according to dynamica ..."
Abstract
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Cited by 778 (71 self)
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We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according
FFTW: An Adaptive Software Architecture For The FFT
, 1998
"... FFT literature has been mostly concerned with minimizing the number of floating-point operations performed by an algorithm. Unfortunately, on present-day microprocessors this measure is far less important than it used to be, and interactions with the processor pipeline and the memory hierarchy have ..."
Abstract
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Cited by 602 (4 self)
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a larger impact on performance. Consequently, one must know the details of a computer architecture in order to design a fast algorithm. In this paper, we propose an adaptive FFT program that tunes the computation automatically for any particular hardware. We compared our program, called FFTW
The adaptive LASSO and its oracle properties
- Journal of the American Statistical Association
"... The lasso is a popular technique for simultaneous estimation and variable selection. Lasso variable selection has been shown to be consistent under certain conditions. In this work we derive a necessary condition for the lasso variable selection to be consistent. Consequently, there exist certain sc ..."
Abstract
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Cited by 683 (10 self)
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as well as if the true underlying model were given in advance. Similar to the lasso, the adaptive lasso is shown to be near-minimax optimal. Furthermore, the adaptive lasso can be solved by the same efficient algorithm for solving the lasso. We also discuss the extension of the adaptive lasso
Adaptive clustering for mobile wireless networks
- IEEE Journal on Selected Areas in Communications
, 1997
"... This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfig ..."
Abstract
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Cited by 561 (11 self)
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reconfigured as nodes move. This network architecture has three main advantages. First, it provides spatial reuse of the bandwidth due to node clustering. Secondly, bandwidth can be shared or reserved in a controlled fashion in each cluster. Finally, the cluster algorithm is robust in the face of topological
Equivariant Adaptive Source Separation
- IEEE Trans. on Signal Processing
, 1996
"... Source separation consists in recovering a set of independent signals when only mixtures with unknown coefficients are observed. This paper introduces a class of adaptive algorithms for source separation which implements an adaptive version of equivariant estimation and is henceforth called EASI (Eq ..."
Abstract
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Cited by 449 (9 self)
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Source separation consists in recovering a set of independent signals when only mixtures with unknown coefficients are observed. This paper introduces a class of adaptive algorithms for source separation which implements an adaptive version of equivariant estimation and is henceforth called EASI
Results 1 - 10
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