/pdf/scalable-molecular-dynamics-with-namd-3j7xyc70g4.pdf

Scalable Molecular Dynamics with NAMD

Data Mining - Concepts and Techniques.

An Introduction to MultiAgent Systems.

to be done in this area. Face recognition is a problem that scarcely clamoured for attention before the computer age but, having surfaced, has involved a wide range of techniques and has attracted the attention of some fine minds (David Mumford was a Fields Medallist in 1974). This singular application of mathematical modelling to a messy applied problem of obvious utility and importance but with no unique solution is a pretty one to share with students: perhaps, returning to the source of our opening quotation, we may invert Duncan's earlier observation, 'There is an art to find the mind's construction in the face!'.

Linear and nonlinear waves, by G. B. Whitham. Pp.636. £50. 1999. ISBN 0 471 35942 4 (Wiley).

1.. HARD CASES 5. Legal Rights A. Legislation . . . We might therefore do well to consider how a philosophical judge might develop, in appropriate cases, theories of what legislative purpose and legal principles require. We shall find that he would construct these theories in the same manner as a philosophical referee would construct the character of a game. I have invented, for this purpose, a lawyer of superhuman skill, learning, patience and acumen, whom I shall call Hercules. I suppose that Hercules is a judge in some representative American jurisdiction. I assume that he accepts the main uncontroversial constitutive and regulative rules of the law in his jurisdiction. He accepts, that is, that statutes have the general power to create and extinguish legal rights, and that judges have the general duty to follow earlier decisions of their court or higher courts whose rationale, as l

Taking Rights Seriously

Unit disk graphs are intersection graphs of circles of unit radius in the plane. We present simple and provably good heuristics for a number of classical NP-hard optimization problems on unit disk graphs. The problems considered include maximum independent set, minimum vertex cover, minimum coloring and minimum dominating set. We also present an on-line coloring heuristic which achieves a competitive ratio of 6 for unit disk graphs. Our heuristics do not need a geometric representation of unit disk graphs. Geometric representations are used only in establishing the performance guarantees of the heuristics. Several of our approximation algorithms can be extended to intersection graphs of circles of arbitrary radii in the plane, intersection graphs of regular polygons, and to intersection graphs of higher dimensional regular objects.

Simple heuristics for unit disk graphs

NC-Approximation Schemes for NP- and PSPACE-Hard Problems for Geometric Graphs

Recent work has looked at extending the k-Means algorithm to incorporate background information in the form of instance level must-link and cannot-link constraints We introduce two ways of specifying additional background information in the form of δ and constraints that operate on all instances but which can be interpreted as conjunctions or disjunctions of instance level constraints and hence are easy to implement We present complexity results for the feasibility of clustering under each type of constraint individually and several types together A key finding is that determining whether there is a feasible solution satisfying all constraints is, in general, NP-complete Thus, an iterative algorithm such as k-Means should not try to find a feasible partitioning at each iteration This motivates our derivation of a new version of the k-Means algorithm that minimizes the constrained vector quantization error but at each iteration does not attempt to satisfy all constraints Using standard UCI datasets, we find that using constraints improves accuracy as others have reported, but we also show that our algorithm reduces the number of iterations until convergence Finally, we illustrate these benefits and our new constraint types on a complex real world object identification problem using the infra-red detector on an Aibo robot

/pdf/clustering-with-constraints-feasibility-issues-and-the-k-4pm5ah2taz.pdf

Clustering with Constraints: Feasibility Issues and the k-Means Algorithm.

The dispersion problem arises in selecting facilities to maximize some function of the distances between the facilities The problem also arises in selecting nondominated solutions for multiobjective decision making It is known to be NP-hard under two objectives: maximizing the minimum distance (MAX-MIN) between any pair of facilities and maximizing the average distance (MAX-AVG) We consider the question of obtaining near-optimal solutions for MAX-MIN, we show that if the distances do not satisfy the triangle inequality, there is no polynomial-time relative approximation algorithm unless P = NP When the distances satisfy the triangle inequality, we analyze an efficient heuristic and show that it provides a performance guarantee of two We also prove that obtaining a performance guarantee of less than two is NP-hard for MAX-AVG, we analyze an efficient heuristic and show that it provides a performance guarantee of four when the distances satisfy the triangle inequality We also present a polynomial-ti

/pdf/heuristic-and-special-case-algorithms-for-dispersion-4cs70840q8.pdf

Heuristic and special case algorithms for dispersion problems

Topology control problems are concerned with the assignment of power values to the nodes of an ad hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing the maximum power and minimizing the total power. A general approach leading to a polynomial algorithm is presented for minimizing maximum power for a class of graph properties called monotone properties. The difficulty of generalizing the approach to properties that are not monotone is discussed. Problems involving the minimization of total power are known to be NP-complete even for simple graph properties. A general approach that leads to an approximation algorithm for minimizing the total power for some monotone properties is presented. Using this approach, a new approximation algorithm for the problem of minimizing the total power for obtaining a 2-node-connected graph is developed. It is shown that this algorithm provides a constant performance guarantee. Experimental results from an implementation of the approximation algorithm are also presented.

/pdf/algorithmic-aspects-of-topology-control-problems-for-ad-hoc-2d33o43fue.pdf

S. S. Ravi

Papers

Simple heuristics for unit disk graphs

NC-Approximation Schemes for NP- and PSPACE-Hard Problems for Geometric Graphs

Clustering with Constraints: Feasibility Issues and the k-Means Algorithm.

Heuristic and special case algorithms for dispersion problems

Algorithmic aspects of topology control problems for ad hoc networks