Deploying and training deep neural networks on mobile devices is a challenging task as machine learning applications increasingly require real-time data processing and on-device training capabilities. the ARM micropro...
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ISBN:
(数字)9798331531836
ISBN:
(纸本)9798331531843
Deploying and training deep neural networks on mobile devices is a challenging task as machine learning applications increasingly require real-time data processing and on-device training capabilities. the ARM microprocessor architecture for mobile devices and embedded systems offers attractive platforms for edge machine learning. there are various machine learning libraries optimized for resource-constrained environments. this paper discusses the TensorFlow Lite library, the process of running and training machine learning models directly on ARM devices using TensorFlow Lite. It discusses the technical implementation, challenges, and optimizations required to achieve efficient training and running of neural network models using mobile devices withthe Aurora operating system as an example. Finally, an example of implementing and training a neural network model on the Aurora OS in the C++ programming language without using additional libraries is given as an alternative to the TensorFlow Lite library.
CS1 programming courses often exhibit low academic performance. One way to address this issue is by implementing early interventions for students. In higher education, various theories have contributed to the topic of...
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We handle finite graphs in two ways, as relational structures on the one hand, and as algebraic objects, i.e., as elements of algebras, based on graph operations on the other.
ISBN:
(纸本)3540412859
We handle finite graphs in two ways, as relational structures on the one hand, and as algebraic objects, i.e., as elements of algebras, based on graph operations on the other.
In this paper we present a binding-time analysis for the logicprogramming language Mercury. Binding-time analysis is a key analysis needed to perform off-line program specialisation. Our analysis deals withthe highe...
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ISBN:
(纸本)3540412859
In this paper we present a binding-time analysis for the logicprogramming language Mercury. Binding-time analysis is a key analysis needed to perform off-line program specialisation. Our analysis deals withthe higher-order aspects of Mercury, and is formulated by means of constraint normalisation. this allows (at least part of) the analysis to be performed on a modular basis.
LPEQ and DLPEQ, two translators for automated equivalence testing of logic programs are discussed. the translators LPEQ and DLPEQ have been implemented in the C programming language under the Linux operating system. B...
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ISBN:
(纸本)354020721X
LPEQ and DLPEQ, two translators for automated equivalence testing of logic programs are discussed. the translators LPEQ and DLPEQ have been implemented in the C programming language under the Linux operating system. Both translators take two logic programs and command line options as their input and produce a translation for equivalence testing as their output. the input files are assumed to be in an internal format, as produced by the front-end LPARSE of the SMODELS system.
作者：
de Groote, PINRIA
LORIA UMR 7503 F-54506 Vandoeuvre Les Nancy France
We reduce the provability of fragments of multiplicative linear logic to matching problems consisting in finding a one-one-correspondence between two sets of first-order terms together with a unifier that equates the ...
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ISBN:
(纸本)3540412859
We reduce the provability of fragments of multiplicative linear logic to matching problems consisting in finding a one-one-correspondence between two sets of first-order terms together with a unifier that equates the corresponding terms. According to the kind of structure to which these first-order terms belong our matching problem corresponds to provability in the implicative fragment of multiplicative linear logic, in the Lambek calculus, or in the non-associative Lambek calculus.
In this paper we define a semantic foundation for an abstract interpretation approach to universal termination and we develop a new abstract domain useful for termination analysis. Based on this approximation we defin...
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ISBN:
(纸本)3540412859
In this paper we define a semantic foundation for an abstract interpretation approach to universal termination and we develop a new abstract domain useful for termination analysis. Based on this approximation we define a method which is able to detect classes of goals which universally terminate (with a fair selection rule). We also define a method which is able to characterize classes of programs and goals for which depth-first search is fair.
the main goal of the paper is to propose a tool for a semantic specification of program updates (in the context of dynamic logicprogramming paradigm). A notion of Kripke structure K-P associated with a generalized lo...
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ISBN:
(纸本)3540412859
the main goal of the paper is to propose a tool for a semantic specification of program updates (in the context of dynamic logicprogramming paradigm). A notion of Kripke structure K-P associated with a generalized logic program P is introduced. It is shown that some paths in K-P specify stable models of P and vice versa, to each stable model of P corresponds a path in K-P. An operation on Kripke structures is defined: for Kripke structures K-P and K-U associated with P (the original program) and U (the updating program), respectively, a Kripke structure K-Pcircle plusU is constructed. K-Pcircle plusU specifies (in a reasonable sense) a set of updates of P by U. there is a variety of possibilities for a selection of an updated program.
Today, there exist many different probabilistic programming languages as well as more inference mechanisms for these languages. Still, most logicprogramming-based languages use backward reasoning based on Selective L...
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Today, there exist many different probabilistic programming languages as well as more inference mechanisms for these languages. Still, most logicprogramming-based languages use backward reasoning based on Selective Linear Definite resolution for inference. While these methods are typically computationally efficient, they often can neither handle infinite and/or continuous distributions nor evidence. To overcome these limitations, we introduce distributional clauses, a variation and extension of Sato's distribution semantics. We also contribute a novel approximate inference method that integrates forward reasoning with importance sampling, a well-known technique for probabilistic inference. In order to achieve efficiency, we integrate two logicprogramming techniques to direct forward sampling. Magic sets are used to focus on relevant parts of the program, while the integration of backward reasoning allows one to identify and avoid regions of the sample space that are inconsistent withthe evidence.
the fourthinternationalconference on logicprogramming and Nonmonotonic reasoning (LPNMR) was held in Dagstuhl, Germany from the 28th to the 31st of July 1997. this year's installment of LPNMR reflected a new st...
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the fourthinternationalconference on logicprogramming and Nonmonotonic reasoning (LPNMR) was held in Dagstuhl, Germany from the 28th to the 31st of July 1997. this year's installment of LPNMR reflected a new stage in the development of this cross-disciplinary field, with demonstrations of ten implemented system joining the submitted papers, invited talks and panel discussions. the details of the conference together withthe various topics tackled are presented.
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