Learning from Interpretation Transition (LFIT) is an unsupervised learning algorithm which learns the dynamics just by observing state transitions. LFIT algorithms have mainly been implemented in the symbolic method, ...
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ISBN:
(数字)9783030974541
ISBN:
(纸本)9783030974541;9783030974534
Learning from Interpretation Transition (LFIT) is an unsupervised learning algorithm which learns the dynamics just by observing state transitions. LFIT algorithms have mainly been implemented in the symbolic method, but they are not robust to noisy or missing data. Recently, research works combining logical operations with neural networks are receiving a lot of attention, with most works taking an extraction based approach where a single neural network model is trained to solve the problem, followed by extracting a logic model from the neural network model. However most research work suffer from the combinatorial explosion problem when trying to scale up to solve larger problems. In particular a lot of the invariance that hold in the symbolic world are not getting utilized in the neural network field. In this work, we present a model that exploits symbolic invariance in our problem. We show that our model is able to scale up to larger tasks than previous work.
Elixir is a new functional programming language whose popularity is rising in the industry. However, there are few works in the literature focused on studying the internal quality of systems implemented in this langua...
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ISBN:
(纸本)9781450392983
Elixir is a new functional programming language whose popularity is rising in the industry. However, there are few works in the literature focused on studying the internal quality of systems implemented in this language. Particularly, to the best of our knowledge, there is currently no catalog of code smells for Elixir. therefore, in this paper, through a grey literature review, we investigate whether Elixir developers discuss code smells. Our preliminary results indicate that 11 of the 22 traditional code smells cataloged by Fowler and Beck are discussed by Elixir developers. We also propose a list of 18 new smells specific for Elixir systems and investigate whether these smells are currently identified by Credo, a well-known static code analysis tool for Elixir. We conclude that only two traditional code smells and one Elixir-specific code smell are automatically detected by this tool. thus, these early results represent an opportunity for extending tools such as Credo to detect code smells and then contribute to improving the internal quality of Elixir systems.
programming interaction usually involves specifying causal relationships such as input events triggering a state change or the propagation of values. Such code may reside in several locations and its execution is driv...
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ISBN:
(纸本)9781450392983
programming interaction usually involves specifying causal relationships such as input events triggering a state change or the propagation of values. Such code may reside in several locations and its execution is driven by multiple causal chains, which hinders the programmer's ability to understand and fix it. We designed Causette, a set of four novel interaction techniques for a code editor. they consist in rearranging causal constructs on demand to make the code representation consistent withthe causal chain being analyzed by the user. We ran an experiment showing that Causette may be more usable than a regular editor for some code understanding tasks. this work suggests that rearranging interaction code may help developers better understand and fix it.
Ontologies - providing an explicit schema for underlying data - often serve as background knowledge for machine learning approaches. Similar to ILP methods, concept learning utilizes such ontologies to learn concept e...
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ISBN:
(数字)9783030974541
ISBN:
(纸本)9783030974541;9783030974534
Ontologies - providing an explicit schema for underlying data - often serve as background knowledge for machine learning approaches. Similar to ILP methods, concept learning utilizes such ontologies to learn concept expressions from examples in a supervised manner. this learning process is usually cast as a search process through the space of ontologically valid concept expressions, guided by heuristics. Such heuristics usually try to balance explorative and exploitative behaviors of the learning algorithms. While exploration ensures a good coverage of the search space, exploitation focuses on those parts of the search space likely to contain accurate concept expressions. However, at their extreme ends, both paradigms are impractical: A totally random explorative approach will only find good solutions by chance, whereas a greedy but myopic, exploitative attempt might easily get trapped in local optima. To combine the advantages of both paradigms, different meta-heuristics have been proposed. In this paper, we examine the Simulated Annealing meta-heuristic and how it can be used to balance the exploration-exploitation trade-off in concept learning. In different experimental settings, we analyse how and where existing concept learning algorithms can benefit from the Simulated Annealing meta-heuristic.
this paper introduces Helix, a distributed system for high-throughput, low-latency large language model (LLM) serving in heterogeneous GPU clusters. the key idea behind Helix is to formulate inference computation of L...
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R is a package-based, multi-paradigm programming language for scientific software. It provides an easy way to install third-party code, datasets, tests, documentation and examples through CRAN (Comprehensive R Archive...
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ISBN:
(纸本)9781450392983
R is a package-based, multi-paradigm programming language for scientific software. It provides an easy way to install third-party code, datasets, tests, documentation and examples through CRAN (Comprehensive R Archive Network). Prior works indicated developers tend to code workarounds to bypass CRAN's automated checks (performed when submitting a package) instead of fixing the code-doing so reduces packages' quality. It may become a threat to those analyses written in R that rely on miss-checked code. this preliminary study card-sorted source code comments and analysed StackOverflow (SO) conversations discussing CRAN checks to understand developers' attitudes. We determined that about a quarter of SO posts aim to bypass a check with a workaround;the most affected are code-related problems, package dependencies, installation and feasibility. We analyse these checks and outline future steps to improve similar automated analyses.
the discovery of memristors has presented a novel paradigm for performing computations within memory, effectively addressing the limitations inherent in von-Neumann architectures. Based on this breakthrough, the utili...
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Complex Event Recognition (CER) systems detect event occurrences in streaming input using predefined event patterns. Techniques that learn event patterns from data are highly desirable in CER. Since such patterns are ...
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Physical side-channel attacks represent a great challenge for today's chip design. Although attacks on CMOS dynamic power represent a class of state-of-the-art attacks, many other effects potentially affect the se...
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this paper presents a novel paradigm, based on carry-look-ahead principles, for finding the negation of a high-precision binary integer represented in two's complement, and also for converting a two's compleme...
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