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304,464
Hamilton cycle decomposition of the Butterfly network
, 1996
"... In this paper, we prove that the wrapped Butterfly graph WBF(d;n) of degree d and dimension n is decomposable into Hamilton cycles. This answers a conjecture of D. Barth and A. Raspaud who solved the case d = 2. ..."
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Cited by 5 (2 self)
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In this paper, we prove that the wrapped Butterfly graph WBF(d;n) of degree d and dimension n is decomposable into Hamilton cycles. This answers a conjecture of D. Barth and A. Raspaud who solved the case d = 2.
Symmetric Hamilton Cycle Decompositions of Complete Graphs Minus a 1Factor
, 2010
"... Let n ≥ 2 be an integer. The complete graph Kn with a 1factor F removed has a decomposition into Hamilton cycles if and only if n is even. We show that Kn − F has a decomposition into Hamilton cycles which are symmetric with respect to the 1factor F if and only if n ≡ 2, 4 mod 8. We also show that ..."
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Let n ≥ 2 be an integer. The complete graph Kn with a 1factor F removed has a decomposition into Hamilton cycles if and only if n is even. We show that Kn − F has a decomposition into Hamilton cycles which are symmetric with respect to the 1factor F if and only if n ≡ 2, 4 mod 8. We also show
TSP tour domination and Hamilton cycle decompositions of regular digraphs
 Oper. Res. Lett
, 1999
"... In this paper, we solve a problem by Glover and Punnen (1997) from the context of domination analysis, where the performance of a heuristic algorithm is rated by the number of solutions that are not better than the solution found by the algorithm, rather than by the relative performance compared ..."
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Cited by 9 (5 self)
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decomposition of regular digraphs. Keywords: ATSP, domination analysis, Hamilton cycle decomposition, regular digraphs 1 Introduction, Terminology and Notation It is well known that most combinatorial optimization problems are NPhard. Due to the lack of polynomial time algorithms to solve NP
Indivisible labor and the business cycle
 Journal of Monetary Economics
, 1985
"... A growth model with shocks to technology is studied. Labor is indivisible, so all variability in hours worked is due to fluctuations in the number employed. We find that, unlike previous equilibrium models of the business cycle, this economy displays large fluctuations in hours worked and relatively ..."
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Cited by 793 (10 self)
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A growth model with shocks to technology is studied. Labor is indivisible, so all variability in hours worked is due to fluctuations in the number employed. We find that, unlike previous equilibrium models of the business cycle, this economy displays large fluctuations in hours worked
A multilinear singular value decomposition
 SIAM J. Matrix Anal. Appl
, 2000
"... Abstract. We discuss a multilinear generalization of the singular value decomposition. There is a strong analogy between several properties of the matrix and the higherorder tensor decomposition; uniqueness, link with the matrix eigenvalue decomposition, firstorder perturbation effects, etc., are ..."
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Cited by 467 (20 self)
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Abstract. We discuss a multilinear generalization of the singular value decomposition. There is a strong analogy between several properties of the matrix and the higherorder tensor decomposition; uniqueness, link with the matrix eigenvalue decomposition, firstorder perturbation effects, etc
House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle
, 2002
"... I develop a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices. Changes in asset prices modify agents ’ borrowing capacity through collateral value; changes in nominal prices affect real repayments through debt deflation. Monetary policy shocks move asse ..."
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Cited by 496 (10 self)
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I develop a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices. Changes in asset prices modify agents ’ borrowing capacity through collateral value; changes in nominal prices affect real repayments through debt deflation. Monetary policy shocks move asset and nominal prices in the same direction, and are amplified and propagated over time. The “financial accelerator ” is not constant across shocks: nominal debt stabilises supply shocks, making the economy less volatile when the central bank controls the interest rate. I discuss the role of equity, debt indexation and household and firm leverage in the propagation mechanism. Finally, I find that monetary policy should not target asset prices as a means of reducing output and inflation volatility.
Training Support Vector Machines: an Application to Face Detection
, 1997
"... We investigate the application of Support Vector Machines (SVMs) in computer vision. SVM is a learning technique developed by V. Vapnik and his team (AT&T Bell Labs.) that can be seen as a new method for training polynomial, neural network, or Radial Basis Functions classifiers. The decision sur ..."
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Cited by 728 (1 self)
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surfaces are found by solving a linearly constrained quadratic programming problem. This optimization problem is challenging because the quadratic form is completely dense and the memory requirements grow with the square of the number of data points. We present a decomposition algorithm that guarantees
Statecharts: A Visual Formalism For Complex Systems
, 1987
"... We present a broad extension of the conventional formalism of state machines and state diagrams, that is relevant to the specification and design of complex discreteevent systems, such as multicomputer realtime systems, communication protocols and digital control units. Our diagrams, which we cal ..."
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Cited by 2683 (56 self)
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alone behavioral description or as part of a more general design methodology that deals also with the system's other aspects, such as functional decomposition and dataflow specification. We also discuss some practical experience that was gained over the last three years in applying the statechart formalism
EEGLAB: an open source toolbox for analysis of singletrial EEG dynamics including independent component analysis
 J. Neurosci. Methods
"... Abstract: We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of singletrial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event i ..."
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Cited by 836 (44 self)
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information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multitrial ERPimage plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), Independent Component Analysis (ICA) and time/frequency decompositions including channel
Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
 Journal of Artificial Intelligence Research
, 2000
"... This paper presents a new approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into a hierarchy of smaller MDPs and decomposing the value function of the target MDP into an additive combination of the value functions of the smaller MDPs. Th ..."
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Cited by 439 (6 self)
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. The decomposition, known as the MAXQ decomposition, has both a procedural semanticsas a subroutine hierarchyand a declarative semanticsas a representation of the value function of a hierarchical policy. MAXQ unifies and extends previous work on hierarchical reinforcement learning by Singh, Kaelbling
Results 1  10
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