OCR17: Ground Truth and Models for 17th c. French Prints (and hopefully more) [PDF]
Journal of Data Mining and Digital Humanities, 2023 Machine learning begins with machine teaching: in the following paper, we present the data that we have prepared to kick-start the training of reliable OCR models for 17th century prints written in French. The construction of a representative corpus is a
Simon Gabay +2 more
doaj +1 more source
Evolving Evolutionary Algorithms with Patterns [PDF]
Soft Computing, Springer-Verlag Vol. 11, Issue 6, pp. 503-518,
2007, 2021 A new model for evolving Evolutionary Algorithms (EAs) is proposed in this paper. The model is based on the Multi Expression Programming (MEP) technique. Each MEP chromosome encodes an evolutionary pattern that is repeatedly used for generating the individuals of a new generation. The evolved pattern is embedded into a standard evolutionary scheme that
arxiv +1 more source
Deep Neuroevolution of Recurrent and Discrete World Models [PDF]
, 2019 Neural architectures inspired by our own human cognitive system, such as the recently introduced world models, have been shown to outperform traditional deep reinforcement learning (RL) methods in a variety of different domains. Instead of the relatively
Asai Masataro +4 more
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Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning [PDF]
, 2022 Interpretability can be critical for the safe and responsible use of machine learning models in high-stakes applications. So far, evolutionary computation (EC), in particular in the form of genetic programming (GP), represents a key enabler for the ...
Alderliesten, Tanja +3 more
core +1 more source
Neural Modelling of Dynamic Systems with Time Delays Based on an Adjusted NEAT Algorithm
, 2023 A problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper.
Laddach, Krzysztof, Łangowski, Rafał
core +1 more source
POWERPLAY: Training an Increasingly General Problem Solver by Continually Searching for the Simplest Still Unsolvable Problem [PDF]
, 2011 Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem ...
Schmidhuber, Jürgen
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An Empirical Study on the Efficacy of Evolutionary Algorithms for Automated Neural Architecture Search [PDF]
, 2022 The configuration and architecture design of neural networks is a time consuming process that has been shown to provide significant training speed and prediction improvements. Traditionally, this process is done manually, but this requires a large amount
Cuccinello, Andrew D.
core +1 more source
, 2018 Universal induction relies on some general search procedure that is doomed to be inefficient. One possibility to achieve both generality and efficiency is to specialize this procedure w.r.t. any given narrow task.
A Graves +7 more
core +1 more source
Optimization of a Hydrodynamic Computational Reservoir through Evolution
, 2023 As demand for computational resources reaches unprecedented levels, research is expanding into the use of complex material substrates for computing. In this study, we interface with a model of a hydrodynamic system, under development by a startup, as a ...
Heiney, Kristine +4 more
core +1 more source
Analysis and FPGA based Implementation of Permutation Binary Neural Networks
, 2023 This paper studies a permutation binary neural network characterized by local binary connections, global permutation connections, and the signum activation function.
Onuki, Mikito +2 more
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