Genetic Programming
20th European Conference, EuroGP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings
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55 Result(s)
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James McDermott
English
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Chapter and Conference Paper
Genetic Programming with Synthetic Data for Interpretable Regression Modelling and Limited Data
A trained regression model can be used to create new synthetic training data by drawing from a distribution over independent variables and calling the model to produce a prediction for the dependent variable. ...
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Article
Open AccessFeature extraction by grammatical evolution for one-class time series classification
When dealing with a new time series classification problem, modellers do not know in advance which features could enable the best classification performance. We propose an evolutionary algorithm based on gramm...
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Chapter
One-Class Subject Authentication Using Feature Extraction by Grammatical Evolution on Accelerometer Data
In this study Grammatical (GE) is used to extract features from accelerometer time in order to increase the performance of a (KDE) classifier. Time series are collected through nine wrist-worn acceler...
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Chapter
Representation Learning for the Arts: A Case Study Using Variational Autoencoders for Drum Loops
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Article
When and Why Metaheuristics Researchers can Ignore “No Free Lunch” Theorems
The No Free Lunch (NFL) theorem for search and optimisation states that averaged across all possible objective functions on a fixed search space, all search algorithms perform equally well. Several refined ver...
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Chapter and Conference Paper
A Multivocal Literature Review of Function-as-a-Service (FaaS) Infrastructures and Implications for Software Developers
In this paper, we provide a multivocal literature review of Function as a Service (FaaS) infrastructures. FaaS is an important, emerging category of cloud computing, which requires that software applications a...
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Chapter
Genetic Programming Symbolic Regression: What Is the Prior on the Prediction?
In the context of Genetic Programming Symbolic Regression, we empirically investigate the prior on the output prediction, that is, the distribution of the output prior to observing data. We distinguish between...
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Chapter and Conference Paper
Program Synthesis in a Continuous Space Using Grammars and Variational Autoencoders
An important but elusive goal of computer scientists is the automatic creation of computer programs given only input and output examples. We present a novel approach to program synthesis based on the combin...
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Article
Open AccessSyngeneic animal models of tobacco-associated oral cancer reveal the activity of in situ anti-CTLA-4
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Tobacco use is the main risk factor for HNSCC, and tobacco-associated HNSCCs have poor prognosis and response to availab...
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Article
Evaluating Dissemination of Adequate Lymphadenectomy for Gastric Cancer in the USA
Adequate lymphadenectomy (AL) of 15+ lymph nodes comprises an important component of gastric cancer surgical therapy. Despite endorsement by the National Comprehensive Cancer Network and the Committee on Cance...
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Article
A genetic algorithm approach to the smart grid tariff design problem
Smart metering in electricity markets offers an opportunity to explore more diverse tariff structures. In this article residential electricity demand and the System Marginal Price of Ireland’s Single Electrici...
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Chapter and Conference Paper
Program Trace Optimization with Constructive Heuristics for Combinatorial Problems
Program Trace Optimisation (PTO), a highly general optimisation framework, is applied to a range of combinatorial optimisation (COP) problems. It effectively combines “smart” problem-specific constructive heur...
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Chapter and Conference Paper
Why Is Auto-Encoding Difficult for Genetic Programming?
Unsupervised learning is an important component in many recent successes in machine learning. The autoencoder neural network is one of the most prominent approaches to unsupervised learning. Here, we use the g...
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Chapter and Conference Paper
Subject Recognition Using Wrist-Worn Triaxial Accelerometer Data
This study demonstrates how a subject can be identified by the means of accelerometer data generated through wrist-worn devices in the context of clinical trials where data integrity is of utmost importance. A...
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Chapter
Geometric Semantic Grammatical Evolution
Geometric Semantic Genetic Programming (GSGP) is a novel form of Genetic Programming (GP), based on a geometric theory of evolutionary algorithms, which directly searches the semantic space of programs. In thi...
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Chapter and Conference Paper
Program Trace Optimization
We introduce Program Trace Optimization (PTO), a system for ‘universal heuristic optimization made easy’. This is achieved by strictly separating the problem from the search algorithm. New problem definitions ...
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Book and Conference Proceedings
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Article
Subtree semantic geometric crossover for genetic programming
The semantic geometric crossover (SGX) proposed by Moraglio et al. has achieved very promising results and received great attention from researchers, but has a significant disadvantage in the exponential growt...
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Book and Conference Proceedings
Genetic Programming
19th European Conference, EuroGP 2016, Porto, Portugal, March 30 - April 1, 2016, Proceedings
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Chapter and Conference Paper
A Hybrid Autoencoder and Density Estimation Model for Anomaly Detection
A novel one-class learning approach is proposed for network anomaly detection based on combining autoencoders and density estimation. An autoencoder attempts to reproduce the input data in the output layer. Th...
