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检索条件"主题词=inference algorithms"

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Bayesian inference in estimation of distribution algorithms

Bayesian inference in estimation of distribution algorithms

引用

Congress on Evolutionary Computation

作者： Marcus Gallagher Ian Wood Jonathan Keith George Sofronov The School of Information Technology and Electrical Engineering University of Queensland Australia The School of Mathematical Sciences Queensland University of Technology Brisbane QLD Australia The Department of Mathematics University of Queensland Australia

Metaheuristics such as Estimation of Distribution algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimization problems. The model fitting task in this class of algorithms has largely been carried out to date based on maximum likelihood. An alternative approach that is prevalent in statistics and machine learning is to use Bayesian inference. In this paper, we provide a framework for the application of Bayesian inference techniques in probabilistic model-based optimization. Based on this framework, a simple continuous Bayesian Estimation of Distribution Algorithm is described. We evaluate and compare this algorithm experimentally with its maximum likelihood equivalent, UMDA G c .

关键词： Bayesian methods inference algorithms Electronic design automation and methodology Machine learning algorithms Maximum likelihood estimation Australia Machine learning Probability density function Optimization methods Statistical distributions

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FUSION OF MULTIPLE LANDMINE DETECTION algorithms USING AN ADAPTIVE NEURO FUZZY inference SYSTEM

FUSION OF MULTIPLE LANDMINE DETECTION ALGORITHMS USING AN AD...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Amine B. Khalifa Hichem Frigui CECS Dept. University of Louisville Louisville KY USA

We present a fusion method, based on fuzzy inference, for detecting buried objects using ground-penetrating radar (GPR) data. The performance of different discrimination algorithms can vary significantly depending on the target type, burial orientation, and other environmental conditions. In some cases, algorithms can provide complementary evidence, while in other cases they can provide contradicting evidence. Thus, effective fusion of these algorithms can achieve higher probability of detection with fewer false alarms. The proposed fusion method is based on an Adaptive Neuro Fuzzy inference System (ANFIS) [1] capable of simultaneously identifying local contexts as well as learning optimal weights for combining local expert discriminators. It is capable of learning meaningful and simple fuzzy rules for different regions of the input space. Results on large and diverse GPR data collections show that the proposed fusion approach can identify local, simple, and meaningful rules capable of non-linear fusion of different discriminators. We also show that the proposed fuzzy inference outperforms other commonly used fusion methods.

关键词： Ground penetrating radar Feature extraction Context inference algorithms Fuzzy logic Buried object detection Histograms

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algorithms and complexity results for #SAT and Bayesian inference

Algorithms and complexity results for #SAT and Bayesian infe...

引用

Annual IEEE Symposium on Foundations of Computer Science

作者： F. Bacchus S. Dalmao T. Pitassi Department of Computer Science University of Toronto Toronto ONT Canada

Bayesian inference is an important problem with numerous applications in probabilistic reasoning. Counting satisfying assignments is a closely related problem of fundamental theoretical importance. In this paper, we show that plain old DPLL equipped with memorization (an algorithm we call #DPLLCache) can solve both of these problems with time complexity that is at least as good as state-of-the-art exact algorithms, and that it can also achieve the best known time-space tradeoff. We then proceed to show that there are instances where #DPLLCache can achieve an exponential speedup over existing algorithms.

关键词： inference algorithms Bayesian methods Computer science Application software Polynomials Government Computational modeling Computer simulation

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inference of gene-regulatory networks using message-passing algorithms

Inference of gene-regulatory networks using message-passing ...

引用

IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

作者： Manohar Shamaiah Sang Hyun Lee Haris Vikalo Department of ECE University of Texas Austin Austin TX USA

We present an application of message-passing techniques to gene regulatory network inference. The network inference is posed as a constrained linear regression problem, and solved by a distributed computationally efficient message-passing algorithm. Performance of the proposed algorithm is tested on gold standard data sets and evaluated using metrics provided by the DREAM2 challenge. Performance of the proposed algorithm is comparable to that of the techniques which yielded the best results in the DREAM2 challenge competition.

关键词： Gene expression Mathematical model Message passing Graphical models inference algorithms Optimization Data models

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Tree-based reparameterization analysis of belief propagation and related algorithms for approximate inference on graphs with cycles

Tree-based reparameterization analysis of belief propagation...

引用

IEEE International Symposium on Information Theory

作者： M. Wainwright T. Jaakkola A. Willsky Department of EECS Massachusetts Institute of Technology Cambridge MA USA

Although it is straightforward to compute the marginals of a distribution p(x) defined by a tree-structured graphical model, this same task is often difficult for graphs with cycles. The belief propagation (BP) or sum-product algorithm is an approximate method for computing such marginals; it is used in various applications (e.g., iterative decoding of turbo and LDPC codes). Belief propagation is typically presented and analyzed as a sequence of message-passing operations. We develop a different conceptual perspective that involves reparameterizing the original distribution in terms of so-called pseudomarginals on cliques of the graph. This view gives rise to a simple characterization of the fixed points, as well as an exact expression and bounds on the error for an arbitrary graph with cycles.

关键词： Algorithm design and analysis Belief propagation Tree graphs inference algorithms Distributed computing Graphical models Sum product algorithm Iterative decoding Parity check codes Markov random fields

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Preliminary Results for GAMI: A Genetic algorithms Approach to Motif inference

Preliminary Results for GAMI: A Genetic Algorithms Approach ...

引用

IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： C.B. Congdon C.W. Fizer N.W. Smith H.R. Gaskins J. Aman G.M. Nava C. Mattingly Department of Computer Science Colby College Waterville ME USA Institute for Genomic Biology University of Illinois Urbana-Champaign Urbana IL USA Mount Desert Island Biological Laboratory Salisbury Cove ME USA

We have developed GAMI, an approach to motif inference that uses a genetic algorithms search and is designed specifically to work with divergent species and possibly long nucleotide sequences. The system design reduces the size of the search space as compared to typical window-location approaches for motif inference. This paper describes the motivation and system design for GAMI, discusses how we have designed the search space and compares this to the search space of other approaches, and presents initial results with data from the literature and from novel tasks. GAMI is able to find a host of putative conserved patterns; possible approaches for validating the utility of the conserved regions are discussed.

关键词： Genetic algorithms Sequences Genomics Bioinformatics Humans Biology inference algorithms Computer science Educational institutions Laboratories

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Protein Secondary Structure Prediction using Bayesian inference method on Decision fusion algorithms

Protein Secondary Structure Prediction using Bayesian Infere...

引用

International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Somasheker Akkaladevi Ajay K Katangur Department of Computer Information Systems Virginia State University Saint Petersburg VA USA Department of Computing Sciences Texas A and M University Corpus Christi Corpus Christi TX USA

Prediction of protein secondary structure (alpha-helix, beta-sheet, coil) from primary sequence of amino acids is a very challenging task, and the problem has been approached from several angles. Previously research was performed in this field using several techniques such as neural networks, simulated annealing (SA) and genetic algorithms (GA) for improving the protein secondary structure prediction accuracy. Decision fusion methods such as the committee method and correlation methods were also used in combination with the profile-based neural networks and AI algorithms for achieving better prediction accuracy. In this research we investigate the Bayesian inference method for predicting the protein secondary structure. The Bayesian inference method proposed in this research uses the results from the committee and correlation methods to achieve better prediction accuracy. Simulations are performed using the RS126 data set. The results show that the protein secondary structure prediction accuracy can be improved by more than 2% using the Bayesian inference method.

关键词： Proteins Bayesian methods inference algorithms Accuracy Neural networks Correlation Coils Amino acids Predictive models Simulated annealing

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A fuzzy inference system for the handoff decision algorithms in the virtual cell layout based tactical communications systems

A fuzzy inference system for the handoff decision algorithms...

引用

MILCOM, Military Communications Conference

作者： T. Onel C. Ersoy E. Cayirci Computer Networks Research Laboratory Bogazici University Istanbul Turkey Wargaming and Simulation Center Turkish War College Istanbul Turkey

A novel handoff decision algorithm, namely multicriteria handoff decision algorithm (MDA), for the virtual cell layout based mobile subsystem of the next generation tactical communications systems is introduced. In this algorithm, handoff decision metrics are received signal strength measurements from the access points, soft capacities of the access points, and relative directions and speeds of the access points and the base transceivers. Soft capacity of an access point is affected by the interference in the environment. We use a fuzzy inference system to process these metrics. We compare our algorithm with the received signal strength based handoff decision algorithms. Our tests have shown that MDA with lowest membership value threshold achieves minimum number of handoffs, and MDA with highest membership value threshold achieves minimum call blocking rate (GoS), where the call blocking rate is still in an acceptable level in the former case and number of handoffs is in an acceptable level in the latter case.

关键词： Fuzzy systems inference algorithms Transceivers Mobile communication Next generation networking Interference Telecommunication traffic Fuzzy logic Artificial neural networks Pattern recognition

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Message Routing and Scheduling in Optical Multistage Networks using Bayesian inference method on AI algorithms

Message Routing and Scheduling in Optical Multistage Network...

引用

International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Ajay K Katangur Somasheker Akkaladevi Department of Computing Sciences Texas A and M University Corpus Christi Corpus Christi TX USA Department of Computer Information Systems Virginia State University Saint Petersburg VA USA

Optical multistage interconnection networks (MINs) suffer from optical-loss during switching and crosstalk problem in the switches. The crosstalk problem is solved by routing messages using time division multiplexing (TDM) approach. This paper focuses on minimizing the number of groups (time slots) required to realize a permutation. Many researchers concentrated on this NP-hard problem and concluded that AI algorithms perform better than the heuristic algorithms. They also showed that majority of the times the performance of genetic algorithm (GA) was better than simulated annealing algorithm (SAA). In this research, we implement a new approach to minimize the number of passes required for scheduling a given permutation. A combinational method is developed which comprises the use of Bayesian inference method on GA and SAA to always guarantee the best solution, instead of only using either GA or SAA. Simulations are performed in Java using multiple threads to run SA and GAA in parallel and to evaluate the performance of the new method. The results are then compared to those obtained from GA and SAA.

关键词： Routing Optical fiber networks Bayesian methods Artificial intelligence inference algorithms Scheduling algorithm Optical crosstalk Optical interconnections Time division multiplexing Multiprocessor interconnection networks

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Message-passing algorithms for channel estimation and decoding using approximate inference

Message-passing algorithms for channel estimation and decodi...

引用

IEEE International Symposium on Information Theory

作者： Mihai-A. Badiu Gunvor E. Kirkelund Carles Navarro Manchón Erwin Riegler Bernard H. Fleury Technical University of Cluj Napoca Romania University of Aalborg Denmark University of Technology Vienna Austria

ISBN: (纸本)9781467325790

We design iterative receiver schemes for a generic communication system by treating channel estimation and information decoding as an inference problem in graphical models. We introduce a recently proposed inference framework that combines belief propagation (BP) and the mean field (MF) approximation and includes these algorithms as special cases. We also show that the expectation propagation and expectation maximization (EM) algorithms can be embedded in the BP-MF framework with slight modifications. By applying the considered inference algorithms to our probabilistic model, we derive four different message-passing receiver schemes. Our numerical evaluation in a wireless scenario demonstrates that the receiver based on the BP-MF framework and its variant based on BP-EM yield the best compromise between performance, computational complexity and numerical stability among all candidate algorithms.

关键词： Receivers inference algorithms Approximation algorithms Vectors Approximation methods Bit error rate Channel estimation

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