autoBOT: evolving neuro-symbolic representations for explainable low resource text classification

DOI10.1007/s10994-021-05968-xOpenAlexW3156197110MaRDI QIDQ2051301

Senja Pollak, Matej Martinc, Blaž Škrlj, Nada Lavrač

Publication date: 24 November 2021

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-021-05968-x

zbMATH Keywords

automlnatural language processingrepresentation learningneuro-symbolic computing

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

autoBOT

Uses Software

• NLTK
• UCI-ml
• LIBSVM
• SciPy
• Scikit
• DEAP
• ConceptNet
• Python
• Spearmint
• TPOT
• Hyperopt
• Auto-WEKA
• Transformers
• BERT
• XLNet
• RoBERTa
• auto-sklearn
• AMC
• Inception-v4
• TextRank
• Autotext
• ML-plan
• RaKUn
• GAMA

Cites Work

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• ML-plan: automated machine learning via hierarchical planning
• How to analyse evolutionary algorithms.
• Propositionalization and embeddings: two sides of the same coin
• On Linear Convergence of a Class of Random Search Algorithms
• The elements of statistical learning. Data mining, inference, and prediction

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