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Bootstrap clustering for graph partitioning

Philippe Gambette, Alain Guénoche (2011)

RAIRO - Operations Research - Recherche Opérationnelle

Given a simple undirected weighted or unweighted graph, we try to cluster the vertex set into communities and also to quantify the robustness of these clusters. For that task, we propose a new method, called bootstrap clustering which consists in (i) defining a new clustering algorithm for graphs, (ii) building a set of graphs similar to the initial one, (iii) applying the clustering method to each of them, making a profile (set) of partitions, (iv) computing a consensus partition for this profile,...

Bootstrap clustering for graph partitioning∗

Philippe Gambette, Alain Guénoche (2012)

RAIRO - Operations Research

Given a simple undirected weighted or unweighted graph, we try to cluster the vertex set into communities and also to quantify the robustness of these clusters. For that task, we propose a new method, called bootstrap clustering which consists in (i) defining a new clustering algorithm for graphs, (ii) building a set of graphs similar to the initial one, (iii) applying the clustering method to each of them, making a profile (set) of partitions, (iv) computing a consensus partition for this profile,...

Bottleneck capacity expansion problems with general budget constraints

Rainer E. Burkard, Bettina Klinz, Jianzhong Zhang (2001)

RAIRO - Operations Research - Recherche Opérationnelle

This paper presents a unified approach for bottleneck capacity expansion problems. In the bottleneck capacity expansion problem, BCEP, we are given a finite ground set E , a family of feasible subsets of E and a nonnegative real capacity c ^ e for all e E . Moreover, we are given monotone increasing cost functions f e for increasing the capacity of the elements e E as well as a budget B . The task is to determine new capacities c e c ^ e such that the objective function given by max F min e F c e is maximized under the side constraint...

Bottleneck Capacity Expansion Problems with General Budget Constraints

Rainer E. Burkard, Bettina Klinz, Jianzhong Zhang (2010)

RAIRO - Operations Research

This paper presents a unified approach for bottleneck capacity expansion problems. In the bottleneck capacity expansion problem, BCEP, we are given a finite ground set E, a family F of feasible subsets of E and a nonnegative real capacity ĉe for all e ∈ E. Moreover, we are given monotone increasing cost functions fe for increasing the capacity of the elements e ∈ E as well as a budget B. The task is to determine new capacities ce ≥ ĉe such that the objective function given by maxF∈Fmine∈Fce...

Bottom-up learning of hierarchical models in a class of deterministic POMDP environments

Hideaki Itoh, Hisao Fukumoto, Hiroshi Wakuya, Tatsuya Furukawa (2015)

International Journal of Applied Mathematics and Computer Science

The theory of partially observable Markov decision processes (POMDPs) is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden...

Boundary-influenced robust controls: two network examples

Martin V. Day (2006)

ESAIM: Control, Optimisation and Calculus of Variations

We consider the differential game associated with robust control of a system in a compact state domain, using Skorokhod dynamics on the boundary. A specific class of problems motivated by queueing network control is considered. A constructive approach to the Hamilton-Jacobi-Isaacs equation is developed which is based on an appropriate family of extremals, including boundary extremals for which the Skorokhod dynamics are active. A number of technical lemmas and a structured verification theorem...

Bound-based decision rules in multistage stochastic programming

Daniel Kuhn, Panos Parpas, Berç Rustem (2008)

Kybernetika

We study bounding approximations for a multistage stochastic program with expected value constraints. Two simpler approximate stochastic programs, which provide upper and lower bounds on the original problem, are obtained by replacing the original stochastic data process by finitely supported approximate processes. We model the original and approximate processes as dependent random vectors on a joint probability space. This probabilistic coupling allows us to transform the optimal solution of the...

Bounded expansion in web graphs

Silvia Gago, Dirk Schlatter (2009)

Commentationes Mathematicae Universitatis Carolinae

In this paper we study various models for web graphs with respect to bounded expansion. All the deterministic models even have constant expansion, whereas the copying model has unbounded expansion. The most interesting case turns out to be the preferential attachment model --- which we conjecture to have unbounded expansion, too.

Bounds on integrals with respect to multivariate copulas

Michael Preischl (2016)

Dependence Modeling

In this paper, we present a method to obtain upper and lower bounds on integrals with respect to copulas by solving the corresponding assignment problems (AP’s). In their 2014 paper, Hofer and Iacó proposed this approach for two dimensions and stated the generalization to arbitrary dimensons as an open problem. We will clarify the connection between copulas and AP’s and thus find an extension to the multidimensional case. Furthermore, we provide convergence statements and, as applications, we consider...

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