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
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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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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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K-Bit-Swap: a new operator for real-coded evolutionary algorithms [PDF]
, 2016 There have been a variety of crossover operators proposed for real-coded genetic algorithms (RCGAs). Such operators recombine values from pairs of strings to generate new solutions.
Marsland, S., Ter-Sarkisov, A.
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Regeneration and Generalization of Cellular Automata through Evolution Strategies [PDF]
, 2021 Cellulære tilstandsmaskiner er systemer av celler som kan demonstrere avansert adferd, bare ved bruk av felles oppdateringsregler og lokal kommunikasjon.
Dalheim, William, Jacobsen, Jonas Brager
core
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
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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.
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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
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, 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
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Towards integrated neural-symbolic systems for human-level AI: Two research programs helping to bridge the gaps [PDF]
, 2015 After a human-level AI-oriented overview of the status quo in neural-symbolic integration, two research programs aiming at overcoming long-standing challenges in the field are suggested to the community: The first program targets a better understanding ...
Besold, T. R., Kuhnberger, K-U.
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