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The Paradigm compiler for distributed-memory multicomputers

P. Banerjee, J.A. Chandy, M. Gupta, E.W. Hodges, J.G. Holm, A. Lain, D.J. Palermo, S. Ramaswamy, E. Su
1995 Computer  
The Paradigm (Parallelizing Compiler for Distributed-Memory, General-Purpose Multicomputers) project at the University of Illinois addresses this problem by developing automatic methods for efficient parallelization  ...  A unified approach efficiently supports regular and irregular computations using data and functional parallelism.  ...  We are also grateful to the National Center for Supercomputing Applications, the San Diego Supercomputing Center, and the Argonne National Laboratory for providing access to their machines.  ... 
doi:10.1109/2.467577 fatcat:ghmtervcfzehzlelvf2ealwgyu

An implementation of narrowing

Alan Josephson, Nachum Dershowitz
1989 The Journal of Logic Programming  
A technique for efficiently identifying redexes, based on the preprocessing of equations for partial matches/unifiers, is presented.  ...  A narrowing, we transform an (uncondi- tional) input  ... 
doi:10.1016/0743-1066(89)90030-7 fatcat:fwfzzbr2vrh6fln6uzwern7biu

Translation of Algebraic Programs into Executable Codes

S. V. Goncharov, A. Ye. Rudich
2005 Cybernetics and Systems Analysis  
In particular, an algorithm for translation of algebraic programs represented in the language Aplan into C codes is proposed.  ...  An algorithm of reconstruction of types in Aplan is considered that also checks the absence of features used for dynamic specification of procedures in a code.  ...  (for example, application is responsible for the "inversion" of a term by an uninterpreted symbol and for a function call).  ... 
doi:10.1007/s10559-006-0014-6 fatcat:nq3yxhjkzzcvhguizdytcri56a

Toward IoT-Friendly Learning Models

Ernesto Damiani, Gabriele Gianini, Michelangelo Ceci, Donato Malerba
2018 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)  
We propose the adoption of an adversarial modeling paradigm across the overall pipeline.  ...  We demonstrate the application of this principle, by a multiple kernel learning approach, based on the exploration of the partition lattice driven by the natural partitioning of the feature set.  ...  As a consequence, one cannot rely on full mutual trust among all the pipeline modules. An adversarial paradigm, based on Game Theory can help in soundly modeling the overall process.  ... 
doi:10.1109/icdcs.2018.00128 dblp:conf/icdcs/DamianiGCM18 fatcat:3vym7eppizfc3m4ibephvclafy

BCI Competition 2003—Data Set IIb: Support Vector Machines for the P300 Speller Paradigm

M. Kaper, P. Meinicke, U. Grossekathoefer, T. Lingner, H. Ritter
2004 IEEE Transactions on Biomedical Engineering  
We propose an approach to analyze data from the P300 speller paradigm using the machine-learning technique support vector machines.  ...  While the classification within the competition is designed for offline analysis, our approach is also well-suited for a real-world online solution: It is fast, requires only 10 electrode positions and  ...  ACKNOWLEDGMENT The authors have used the SVM algorithm from the libsvm toolbox by Chang and Lin [13] . They would like to thank P. McGuire for his careful reading of the final version of the paper.  ... 
doi:10.1109/tbme.2004.826698 pmid:15188881 fatcat:slmq5may7bhnbkmlr3zq7fn4ly

Decomposition Without Regret [article]

Weixin Zhang, Cristina David, Meng Wang
2022 arXiv   pre-print
Programming languages are embracing both functional and object-oriented paradigms. A key difference between the two paradigms is the way of achieving data abstraction.  ...  We prove that the transformation preserves the type and semantics of the original program.  ...  Furthermore, studying the transformation between the two styles can provide a theoretical foundation for compiling multi-paradigm languages into single-paradigm ones.  ... 
arXiv:2204.10411v1 fatcat:bmtsggflwbdffctj7lzdvrmxty

Using a Low-Power Spiking Continuous Time Neuron (SCTN) for Sound Signal Processing

Moshe Bensimon, Shlomo Greenberg, Moshe Haiut
2021 Sensors  
This work also demonstrates an efficient hardware implementation of the SNN network based on the low-power Spike Continuous Time Neuron (SCTN).  ...  This work presents a new approach based on a spiking neural network for sound preprocessing and classification.  ...  This work presents a new approach based on a spiking neural network for sound preprocessing and classification.  ... 
doi:10.3390/s21041065 pmid:33557214 pmcid:PMC7913968 fatcat:qhpnb47ahbcchluzuofyx5rat4

Model Construction for Knowledge-Intensive Engineering Tasks [chapter]

Benno Stein
2008 Studies in Computational Intelligence  
The starting point for an engineering task is a given system, S, or a set of systems, S, along with a shortcoming of information, often formulated as a question: • Which component is broken in S?  ...  (diagnosis ∼ analysis) • How does S react on the input u? (simulation ∼ analysis) • Does a system with the desired functionality exist in S? (design ∼ synthesis)  ...  Heuristics for resource selection are derived from graph-theoretical considerations which base on the analysis of the strong components in the dependency graph.  ... 
doi:10.1007/978-3-540-78297-1_7 fatcat:ddozeyfbzrczjhovkw7gioa5ua

Proposing a Features Preprocessing Method Based on Artificial Immune and Minimum Classification Errors Methods

M. Miralvand, S. Rasoolzadeh, M. Majidi
2015 Journal of Applied Research and Technology  
Comparison of results of proposed method with other preprocessing methods shows the superiority of the proposed method so that in 90% of cases it has the best performance based on different measures.  ...  In particular artificial immune systems have been used for computing the mapping matrices and improving features.  ...  One of the features transformation methods is based on Minimum Classification Error (MCE) algorithms [7] .  ... 
doi:10.1016/s1665-6423(15)30009-2 fatcat:wjjjysgn6fftfcz6yziiwrhz4i

A survey of preprocessing methods used for analysis of big data originated from smart grids

Turki Ali Alghamdi, Nadeem Javaid
2022 IEEE Access  
The data is essential for electricity demand, generation and price forecasting, which plays an important role in making energy efficient decisions, and long and short term predictions regarding energy  ...  Moreover, based on the discussion of the data preprocessing methods, a narrative is built with a critical analysis. Finally, future research directions are discussed to guide the readers.  ...  Hence, different preprocessing methods are proposed by researchers for feature extraction. The main focus of [33] is subspace feature extraction methods based on the loss function.  ... 
doi:10.1109/access.2022.3157941 fatcat:s2wn3z37zvay3lwwrw3jed64se

Proposing a features preprocessing method based on artificial immune and minimum classification errors methods

M. Miralvand, S. Rasoolzadeh, M. Majidi
2015 Journal of Applied Research and Technology  
Comparison of results of proposed method with other preprocessing methods shows the superiority of the proposed method so that in 90% of cases it has the best performance based on different measures.  ...  In particular, artificial immune systems have been used for computing the mapping matrices and improving features.  ...  In this method that is implemented for some iteration, in each step a MCE algorithms are efficient and effective methods of feature transformation and have many applications in the fields of data mining  ... 
doi:10.1016/j.jart.2015.09.005 fatcat:lxjgow6fhvffzn3q4wok7voy34

Two Transformations of Clauses into Constraints and Their Properties for Cost-Based Hypothetical Reasoning [chapter]

Yutaka Matsuo, Mitsuru Ishizuka
2002 Lecture Notes in Computer Science  
We are mainly targeting at cost-based hypothetical reasoning (or abduction), but through preprocessing, the discussion has generality.  ...  The first transformation, which translates constraints into linear inequalities, has been applied to cost-based abduction in the past and showed good performance.  ...  An efficient engine for propositional cost-based abduction plays an crucial role in such systems.  ... 
doi:10.1007/3-540-45683-x_15 fatcat:vfunjp63kzak7mhbm6zh7ap33a

Using Natural Language Preprocessing Architecture (NLPA) for Big Data Text Sources

María Novo-Lourés, Reyes Pavón, Rosalía Laza, David Ruano-Ordas, Jose R. Méndez
2020 Scientific Programming  
Keeping this in mind, we combined a pipelining framework (BDP4J (Big Data Pipelining For Java)) with the implementation of a set of text preprocessing techniques in order to create NLPA (Natural Language  ...  Preprocessing Architecture), an extendable open-source plugin implementing preprocessing steps that can be easily combined to create a pipeline.  ...  FeatureVector compiles a set of features of text properties (synset-based or token-based), identified in the text of an instance, and their values.  ... 
doi:10.1155/2020/2390941 fatcat:4coynlja45fw5nebufhsqwcmna

Advanced compilation techniques in the PARADIGM compiler for distributed-memory multicomputers

Ernesto Su, Antonio Lain, Shankar Ramaswamy, Daniel J. Palermo, Eugene W. Hodges, Prithviraj Banerjee
1995 Proceedings of the 9th international conference on Supercomputing - ICS '95  
The PARADIGM compiler project provides an automated means to parallelize programs, written in a serial programming model, for efficient execution on distributed-memory muiticomputers.  ...  A previous implementation of the compiler based on the PTD representation allowed symbolic array sizes, affine loop bounds and array subscripts, and variable number of processors, provided that arrays  ...  S3.50 The PARADIGM project at the University of Illinois addresses this problem by developing an automated means t'o parallelize and optimize sequential programs for efficient execution on muiticomputers  ... 
doi:10.1145/224538.224650 dblp:conf/ics/SuLRPHB95 fatcat:dltpt2v4sbcxlcrxoopv6rphqq

Trace transform based method for color image domain identification [article]

Igor G. Olaizola and Marco Quartulli and Julian Florez and Basilio Sierra
2019 arXiv   pre-print
In this paper, we introduce a new color image context categorization method (DITEC) based on the trace transform.  ...  Context categorization is a fundamental pre-requisite for multi-domain multimedia content analysis applications in order to manage contextual information in an efficient manner.  ...  These sinusoidal signals encode the preprocessed image I with a given level of distortion depending on the functional and quantization parameters.  ... 
arXiv:1208.3901v3 fatcat:kqyefvoyirajtbt4aeouidcl4e
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