16,288 research outputs found
A practical application of simulated annealing to clustering
Abstract--We formalize clustering as a partitioning problem with a user-defined internal clustering criterion and present SINICC, an unbiased, empirical method for comparing internal clustering criteria. An application to multi-sensor fusion is described, where the data set is composed of inexact sensor "reports" pertaining to "objects" in an environment. Given these reports, the objective is to produce a representation of the environment, where each entity in the representation is the result of "fusing" sensor reports. Before one can perform fusion, however, the reports must be "associated" into homogeneous clusters. Simulated annealing is used to find a near-optimal partitioning with respect to each of several clustering criteria for a variety of simulated data sets. This method can then be used to determine the "best" clustering criterion for the multi-sensor fusion problem with a given fusion operator
Deterministic Annealing as a jet clustering algorithm in hadronic collisions
We show that a general purpose clusterization algorithm, Deterministic
Annealing, can be adapted to the problem of jet identification in particle
production by high energy collisions. In particular we consider the problem of
jet searching in events generated at hadronic colliders. Deterministic
Annealing is able to reproduce the results obtained by traditional jet
algorithms and to exhibit a higher degree of flexibility.Comment: 13 pages, 6 figure
Global Optimization strategies for two-mode clustering
Two-mode clustering is a relatively new form of clustering that clusters both rows and columns of a data matrix. To do so, a criterion similar to k-means is optimized. However, it is still unclear which optimization method should be used to perform two-mode clustering, as various methods may lead to non-global optima. This paper reviews and compares several optimization methods for two-mode clustering. Several known algorithms are discussed and a new, fuzzy algorithm is introduced. The meta-heuristics Multistart, Simulated Annealing, and Tabu Search are used in combination with these algorithms. The new, fuzzy algorithm is based on the fuzzy c-means algorithm of Bezdek (1981) and the Fuzzy Steps approach to avoid local minima of Heiser and Groenen (1997) and Groenen and Jajuga (2001). The performance of all methods is compared in a large simulation study. It is found that using a Multistart meta-heuristic in combination with a two-mode k-means algorithm or the fuzzy algorithm often gives the best results. Finally, an empirical data set is used to give a practical example of two-mode clustering.algorithms;fuzzy clustering;multistart;simulated annealing;simulation;tabu search;two-mode clustering
Robust designs for Poisson regression models
We consider the problem of how to construct robust designs for Poisson regression models. An analytical expression is derived for robust designs for first-order Poisson regression models where uncertainty exists in the prior parameter estimates. Given certain constraints in the methodology, it may be necessary to extend the robust designs for implementation in practical experiments. With these extensions, our methodology constructs designs which perform similarly, in terms of estimation, to current techniques, and offers the solution in a more timely manner. We further apply this analytic result to cases where uncertainty exists in the linear predictor. The application of this methodology to practical design problems such as screening experiments is explored. Given the minimal prior knowledge that is usually available when conducting such experiments, it is recommended to derive designs robust across a variety of systems. However, incorporating such uncertainty into the design process can be a computationally intense exercise. Hence, our analytic approach is explored as an alternative
Track clustering with a quantum annealer for primary vertex reconstruction at hadron colliders
Clustering of charged particle tracks along the beam axis is the first step
in reconstructing the positions of hadronic interactions, also known as primary
vertices, at hadron collider experiments. We use a 2036 qubit D-Wave quantum
annealer to perform track clustering in a limited capacity on artificial events
where the positions of primary vertices and tracks resemble those measured by
the Compact Muon Solenoid experiment at the Large Hadron Collider. The
algorithm, which is not a classical-quantum hybrid but relies entirely on
quantum annealing, is tested on a variety of event topologies from 2 primary
vertices and 10 tracks up to 5 primary vertices and 15 tracks. It is
benchmarked against simulated annealing executed on a commercial CPU
constrained to the same processor time per anneal as time in the physical
annealer, and performance is found to be comparable for small numbers of
vertices with an intriguing advantage noted for 2 vertices and 16 tracks
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Survey of partitioning techniques in silicon compilation
In the silicon compilation design process, partitioning is usually the first problem to be investigated because partitioning algorithms form the backbone of many algorithms including: system synthesis, processor synthesis, floorplanning, and placement. In this survey, several partitioning techniques will be examined. In addition, this paper will review the partitioning algorithms used by synthesis systems at different design levels
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Automatic synthesis of analog layout : a survey
A review of recent research in the automatic synthesis of physical geometry for analog integrated circuits is presented. On introduction, an explanation of the difficulties involved in analog layout as opposed to digital layout is covered. Review of the literature then follows. Emphasis is placed on the exposition of general methods for addressing problems specific to analog layout, with the details of specific systems only being given when they surve to illustrate these methods well. The conclusion discusses problems remaining and offers a prediction as to how technology will evolve to solve them. It is argued that although progress has been and will continue to be made in the automation of analog IC layout, due to fundamental differences in the nature of analog IC design as opposed to digital design, it should not be expected that the level of automation of the former will reach that of the latter any time soon
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