Literatur: Unterschied zwischen den Versionen
(Die Seite wurde neu angelegt: „<div class="thebibliography"> Richard O Duda, Peter E. Hart, David G. Stork. ''Pattern Classification''. John Wiley & Sons, 2001. Nazmul Siddique, Hojjat Adeli. ''Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing''. John Wiley & Sons, 2013. Luciano Floridi, Josh Cowls: . In: . In ''Harvard Data Science Review'', Band 1, Nr. 1, 2019. doi:10.1162/99608f92.8cd550d1 Jacob Devlin, Ming-Wei Cha…“) |
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Richard O Duda, Peter E. Hart, David G. Stork. ''Pattern Classification''. John Wiley & Sons, 2001. | [Duda et al.(2001)] Richard O Duda, Peter E. Hart, David G. Stork. ''Pattern Classification''. John Wiley & Sons, 2001. | ||
Nazmul Siddique, Hojjat Adeli. ''Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing''. John Wiley & Sons, 2013. | [Siddique et al.(2013)] Nazmul Siddique, Hojjat Adeli. ''Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing''. John Wiley & Sons, 2013. | ||
Luciano Floridi, Josh Cowls: | [FloridiCowls(2019)]Luciano Floridi, Josh Cowls: A Unified Framework of Five Principles for AI in Society. In ''Harvard Data Science Review'', Band 1, Nr. 1, 2019. doi:10.1162/99608f92.8cd550d1 | ||
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In ''North American Chapter of the Association for Computational Linguistics: Human Language Technologies.'', 2019. | [Devlin et al.(2019)] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In ''North American Chapter of the Association for Computational Linguistics: Human Language Technologies.'', 2019. | ||
Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. Distributed Representations of Words and Phrases and their Compositionality. In ''NIPS.'', 2013. | [Mikolov et al.(2013)] Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. Distributed Representations of Words and Phrases and their Compositionality. In ''NIPS.'', 2013. | ||
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. Attention is all you need. In ''Advances in neural information processing systems, 30'', 2017. | [Vaswani et al.(2017)] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. Attention is all you need. In ''Advances in neural information processing systems, 30'', 2017. | ||
Ikuya Yamada, Akari Asai, Jin Sakuma, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji, and Yuji Matsumoto. Wikipedia2vec: An efficient toolkit for learning and visualizing the embeddings of words and entities from wikipedia. In ''arXiv preprint arXiv:1812.06280'', 2018. | [Yamada et al.(2018)] Ikuya Yamada, Akari Asai, Jin Sakuma, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji, and Yuji Matsumoto. Wikipedia2vec: An efficient toolkit for learning and visualizing the embeddings of words and entities from wikipedia. In ''arXiv preprint arXiv:1812.06280'', 2018. | ||
Yoshua Bengio. . ''Scholarpedia.'', 3:3881, 2008. https://doi.org/10.4249/scholarpedia.3881 | [Bengio(2008)] Yoshua Bengio. Neural net language models. ''Scholarpedia.'', 3:3881, 2008. https://doi.org/10.4249/scholarpedia.3881 | ||
G. A Miller. . ''Commun. ACM'', 38(11), 39-41, Nov. 1995. | [3] G. A Miller. WordNet: A Lexical Database for English. ''Commun. ACM'', 38(11), 39-41, Nov. 1995. | ||
O. Bodenreider. . ''Nucleic Acids Research'', 32, no. Database issue, D267–270, Jan. 2004. | [4] O. Bodenreider. The Unified Medical Language System (UMLS): integrating biomedical terminology. ''Nucleic Acids Research'', 32, no. Database issue, D267–270, Jan. 2004. | ||
K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor. . In ''Proceedings of the 2008 ACM SIGMOD international conference on Management of data. ACM'', 1247–1250, 2008. | [5] K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor. Freebase: a collaboratively created graph database for structuring human knowledge. In ''Proceedings of the 2008 ACM SIGMOD international conference on Management of data. ACM'', 1247–1250, 2008. | ||
D. Vrandecic and M. Krötzsch. . ''Communications of the ACM'', 57(10), 78–85, 2014. | [6] D. Vrandecic and M. Krötzsch. Wikidata: a free collaborative knowledgebase. ''Communications of the ACM'', 57(10), 78–85, 2014. | ||
J. Hoffart, F. M. Suchanek, K. Berberich, and G. Weikum. . ''Artificial Intelligence'', 194, 28–61, 2013. | [1] J. Hoffart, F. M. Suchanek, K. Berberich, and G. Weikum. YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. ''Artificial Intelligence'', 194, 28–61, 2013. | ||
S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives. ''DBpedia: A Nucleus for a Web of Open Data''. in The Semantic Web. Springer Berlin Heidelberg, vol. 4825, pp. 722–735, 2007. | [7] S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives. ''DBpedia: A Nucleus for a Web of Open Data''. in The Semantic Web. Springer Berlin Heidelberg, vol. 4825, pp. 722–735, 2007. | ||
A. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. H. Jr, and T. M. Mitchell. . In ''Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI 2010), AAAI Press'', 1306–1313, 2010. | [8] A. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. H. Jr, and T. M. Mitchell. Toward an Architecture for Never-Ending Language Learning. In ''Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI 2010), AAAI Press'', 1306–1313, 2010. | ||
X. Dong, E. Gabrilovich, G. Heitz, W. Horn, N. Lao, K. Murphy, T. Strohmann, S. Sun, and W. Zhang. . In ''Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM'', 601–610, 2014. | [2] X. Dong, E. Gabrilovich, G. Heitz, W. Horn, N. Lao, K. Murphy, T. Strohmann, S. Sun, and W. Zhang. Knowledge Vault: A Web-scale Approach to Probabilistic Knowledge Fusion. In ''Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM'', 601–610, 2014. | ||
J. Fan, D. Ferrucci, D. Gondek, and A. Kalyanpur, . In ''Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading, Association for Computational Linguistics'', 122–127, 2010. | [9] J. Fan, D. Ferrucci, D. Gondek, and A. Kalyanpur, Prismatic: Inducing knowledge from a large scale lexicalized relation resource. In ''Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading, Association for Computational Linguistics'', 122–127, 2010. | ||
Russa. Biswas. ''Embedding Based Link Prediction for Knowledge Graph Completion. Ph. D. dissertation''. PhD thesis, Karlsruher Institut für Technologie (KIT), Germany, 2003. https://doi.org/10.5445/IR/1000156436 | [Biswas(2003)] Russa. Biswas. ''Embedding Based Link Prediction for Knowledge Graph Completion. Ph. D. dissertation''. PhD thesis, Karlsruher Institut für Technologie (KIT), Germany, 2003. https://doi.org/10.5445/IR/1000156436 | ||
S. Ji, S. Pan, E. Cambria, P. Marttinen and P. S. Yu,. . In ''IEEE Transactions on Neural Networks and Learning Systems'', 33(2),494-514, 2022. doi: 10.1109/TNNLS.2021.3070843 | [Ji et al.(2022)] S. Ji, S. Pan, E. Cambria, P. Marttinen and P. S. Yu,. A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. In ''IEEE Transactions on Neural Networks and Learning Systems'', 33(2),494-514, 2022. doi: 10.1109/TNNLS.2021.3070843 | ||
M. Nickel, K. .Murphy, V. Tresp, and E. Gabrilovich. . In ''Proceedings of the IEEE, Institute of Electrical and Electronics Engineers (IEEE)'', 104(1):11-33, 2016. http://dx.doi.org/10.1109/JPROC.2015.2483592 | [Nickel et al.(2016)] M. Nickel, K. .Murphy, V. Tresp, and E. Gabrilovich. A Review of Relational Machine Learning for Knowledge Graphs. In ''Proceedings of the IEEE, Institute of Electrical and Electronics Engineers (IEEE)'', 104(1):11-33, 2016. http://dx.doi.org/10.1109/JPROC.2015.2483592 | ||
Mayank Kejriwal. . ''Information'', 13(4), 161, 1-17, 2022. https://doi.org/10.3390/info13040161 | [Kejriwal(2022)] Mayank Kejriwal. Knowledge Graphs: A Practical Review of the Research Landscape. ''Information'', 13(4), 161, 1-17, 2022. https://doi.org/10.3390/info13040161 | ||
Maximilian Pflueger, David J. Tena Cucala, and Egor V. Kostylev. . In ''The Semantic Web – ISWC 2022, Springer International Publishing'', 481–497, 2022. | [Pflueger et al.(2022)] Maximilian Pflueger, David J. Tena Cucala, and Egor V. Kostylev. GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. In ''The Semantic Web – ISWC 2022, Springer International Publishing'', 481–497, 2022. | ||
Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. . ''IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers (IEEE)'', 56(4), 1–20, 2024. http://dx.doi.org/10.1109/TKDE.2024.3352100 | [Pan et al.(2024)] Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. Unifying Large Language Models and Knowledge Graphs: A Roadmap. ''IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers (IEEE)'', 56(4), 1–20, 2024. http://dx.doi.org/10.1109/TKDE.2024.3352100 | ||
Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, and Xindong Wu. . ''ACM Computing Surveys'', 56(4), Article No.: 94, 1–62, 2023. https://doi.org/10.1145/3618295 | [Zhong et al.(2023)] Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, and Xindong Wu. A Comprehensive Survey on Automatic Knowledge Graph Construction. ''ACM Computing Surveys'', 56(4), Article No.: 94, 1–62, 2023. https://doi.org/10.1145/3618295 | ||
[Fisher(1936)] R.A. Fisher. The Use of Multiple Measurements in Taxonomic Problems. ''Annals of Eugenics.'', 7 (2): 179–188, 1963. https://doi:10.1111/j.1469-1809.1936.tb02137.x. | |||
[Vapnik and Chervonenkis(1971)] V. N. Vapnik, and A. Y. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. ''Theory of Probability and Its Applications'', 16, 264–280, 1971. | |||
[Blumer et al.(1989)] A. Blumer, A. Ehrenfeucht, D. Haussler, and M. K. Warmuth. Learnability and the Vapnik–Chervonenkis dimension. ''Journal of the ACM'', 36(4), 929––865, 1989. | |||
[Vapnik(1995)] V. N. Vapnik. ''The Nature of Statistical Learning Theory''. Springer, New York., 1995. | |||
[Wolpert9(1996)] D. H. Wolpert. The lack of a priori distinction between learning algorithms. ''Neural Computation'', 8(7), 1341–1390, 1996. | |||
[McCulloch and Pitts(1943)] W. S. McCulloch and W. Pitts. A logical calculus of ideas immanent in nervous activity. ''Bulletin of Mathematical Biophysics'', 5, 115–133, 1943. | |||
[Rosenblatt(1958)] Frank Rosenblatt. The perceptron. A probabilistic model for information storage and organization in the brain. ''Psychological Reviews'', 65, 386–408, 1958. | |||
[Goodfellow et al.(2016)] I. Goodfellow, Y. Bengio, and A. Courville. ''Deep Learning''. MIT Press, 2016. | |||
[Reynolds(2021)] Anh Reynolds. ''Understanding convolutional neural networks (cnns).'' https://anhreynolds.com/blogs/cnn.html, 2021 Accessed: 2024-02-11. | |||
[JurafskyMartin(2023)] Daniel Jurafsky and James H. Martin. ''Speech and Language Processing''. https://web.stanford.edu/ jurafsky/slp3, 2023 | |||
[Hochreiter(1991)] S. Hochreiter. ''Untersuchungen zu dynamischen neuronalen Netzen. Diplom thesis''. Diplom thesis, Institut f. Informatik, Technische Univ. Munich., Germany, 1991. | |||
[CARTPennStateCourse(2024)] Penn State’s Department of Statistics. ''Course notes for STAT 508: Applied Data Mining and Statistical Learning, Lesson 11''. https://online.stat.psu.edu/stat508/, 2024 Creative Commons license CC BY-NC 4.0 | |||
[Breiman(1996)] Leo Breiman. Bagging predictors. ''Machine Learning'', 24(2), 123–140, 1996. doi:10.1007/BF00058655 | |||
[Elman(1990)] J. L. Elman. Finding structure in time. ''Cognitive science'', 14(2), 179–211, 1990. | |||
[Werbos(1974)] P. Werbos. ''Beyond regression: new tools for prediction and analysis in the behavioral sciences. Ph.D. thesis''. Ph.D. thesis, Harvard University, USA, 1974. | |||
[SchusterPaliwal(1997)] M. Schuster and K. K. Paliwal. Bidirectional recurrent neural networks. ''IEEE Transactions on Signal Processing'', 45, 2673–2681, 1997. | |||
[HochreiterSchmidhuber(1997)] S. Hochreiter and J. Schmidhuber. Long short-term memory. ''Neural Computation'', 9(8),1735–1780, 1997. | |||
[Bellman(1957)] Richard Bellman. A Markovian Decision Process. ''Journal of Mathematics and Mechanics'', 6(5):679–684, 1957. http://www.jstor.org/stable/24900506 | |||
[Bertsekas(1987)] Dimitri P. Bertsekas. Dynamic Programming: Deterministic and Stochastic Models. Prentice-Hall, 1987. | |||
[LittmanDeanKaelbling(1995)] M. L. Littman, T. L. Dean, and L. P. Kaelbling. On the complexity of solving Markov decision problems. In ''Proceedings of the Eleventh Annual Conference on Uncertainty in Articial Intelligence (UAI-95)'', Montreal, Québec, Canada, 1995. | |||
[Li(2018)] Y. Li. Deep reinforcement learning. . https://arxiv.org/abs/1810.06339 arXiv:1810.06339 | |||
[Son et al.(2022)] Ki Young Son, Jongwoo Ko, Eunseok Kim, Si Young Lee, Min-Ji Kim, Jisang Han, Eunhae Shin, Tae-Young Chung, and Dong Hui Lim. Deep learningbased cataract detection and grading from slit-lamp and retro-illumination | |||
photographs: Model development and validation study.. ''Ophthalmology Science'', 2(2), 2022. | |||
Ki Young Son, Jongwoo Ko, Eunseok Kim, Si Young Lee, Min-Ji Kim, Jisang Han, Eunhae Shin, Tae-Young Chung, and Dong Hui Lim. . ''Ophthalmology Science'', 2(2), 2022. | |||
</div> | </div> |
Version vom 15. September 2024, 01:25 Uhr
[Duda et al.(2001)] Richard O Duda, Peter E. Hart, David G. Stork. Pattern Classification. John Wiley & Sons, 2001.
[Siddique et al.(2013)] Nazmul Siddique, Hojjat Adeli. Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing. John Wiley & Sons, 2013.
[FloridiCowls(2019)]Luciano Floridi, Josh Cowls: A Unified Framework of Five Principles for AI in Society. In Harvard Data Science Review, Band 1, Nr. 1, 2019. doi:10.1162/99608f92.8cd550d1
[Devlin et al.(2019)] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In North American Chapter of the Association for Computational Linguistics: Human Language Technologies., 2019.
[Mikolov et al.(2013)] Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. Distributed Representations of Words and Phrases and their Compositionality. In NIPS., 2013.
[Vaswani et al.(2017)] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Advances in neural information processing systems, 30, 2017.
[Yamada et al.(2018)] Ikuya Yamada, Akari Asai, Jin Sakuma, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji, and Yuji Matsumoto. Wikipedia2vec: An efficient toolkit for learning and visualizing the embeddings of words and entities from wikipedia. In arXiv preprint arXiv:1812.06280, 2018.
[Bengio(2008)] Yoshua Bengio. Neural net language models. Scholarpedia., 3:3881, 2008. https://doi.org/10.4249/scholarpedia.3881
[3] G. A Miller. WordNet: A Lexical Database for English. Commun. ACM, 38(11), 39-41, Nov. 1995.
[4] O. Bodenreider. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Research, 32, no. Database issue, D267–270, Jan. 2004.
[5] K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor. Freebase: a collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data. ACM, 1247–1250, 2008.
[6] D. Vrandecic and M. Krötzsch. Wikidata: a free collaborative knowledgebase. Communications of the ACM, 57(10), 78–85, 2014.
[1] J. Hoffart, F. M. Suchanek, K. Berberich, and G. Weikum. YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. Artificial Intelligence, 194, 28–61, 2013.
[7] S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives. DBpedia: A Nucleus for a Web of Open Data. in The Semantic Web. Springer Berlin Heidelberg, vol. 4825, pp. 722–735, 2007.
[8] A. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. H. Jr, and T. M. Mitchell. Toward an Architecture for Never-Ending Language Learning. In Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI 2010), AAAI Press, 1306–1313, 2010.
[2] X. Dong, E. Gabrilovich, G. Heitz, W. Horn, N. Lao, K. Murphy, T. Strohmann, S. Sun, and W. Zhang. Knowledge Vault: A Web-scale Approach to Probabilistic Knowledge Fusion. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 601–610, 2014.
[9] J. Fan, D. Ferrucci, D. Gondek, and A. Kalyanpur, Prismatic: Inducing knowledge from a large scale lexicalized relation resource. In Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading, Association for Computational Linguistics, 122–127, 2010.
[Biswas(2003)] Russa. Biswas. Embedding Based Link Prediction for Knowledge Graph Completion. Ph. D. dissertation. PhD thesis, Karlsruher Institut für Technologie (KIT), Germany, 2003. https://doi.org/10.5445/IR/1000156436
[Ji et al.(2022)] S. Ji, S. Pan, E. Cambria, P. Marttinen and P. S. Yu,. A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. In IEEE Transactions on Neural Networks and Learning Systems, 33(2),494-514, 2022. doi: 10.1109/TNNLS.2021.3070843
[Nickel et al.(2016)] M. Nickel, K. .Murphy, V. Tresp, and E. Gabrilovich. A Review of Relational Machine Learning for Knowledge Graphs. In Proceedings of the IEEE, Institute of Electrical and Electronics Engineers (IEEE), 104(1):11-33, 2016. http://dx.doi.org/10.1109/JPROC.2015.2483592
[Kejriwal(2022)] Mayank Kejriwal. Knowledge Graphs: A Practical Review of the Research Landscape. Information, 13(4), 161, 1-17, 2022. https://doi.org/10.3390/info13040161
[Pflueger et al.(2022)] Maximilian Pflueger, David J. Tena Cucala, and Egor V. Kostylev. GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. In The Semantic Web – ISWC 2022, Springer International Publishing, 481–497, 2022.
[Pan et al.(2024)] Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. Unifying Large Language Models and Knowledge Graphs: A Roadmap. IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers (IEEE), 56(4), 1–20, 2024. http://dx.doi.org/10.1109/TKDE.2024.3352100
[Zhong et al.(2023)] Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, and Xindong Wu. A Comprehensive Survey on Automatic Knowledge Graph Construction. ACM Computing Surveys, 56(4), Article No.: 94, 1–62, 2023. https://doi.org/10.1145/3618295
[Fisher(1936)] R.A. Fisher. The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics., 7 (2): 179–188, 1963. https://doi:10.1111/j.1469-1809.1936.tb02137.x.
[Vapnik and Chervonenkis(1971)] V. N. Vapnik, and A. Y. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and Its Applications, 16, 264–280, 1971.
[Blumer et al.(1989)] A. Blumer, A. Ehrenfeucht, D. Haussler, and M. K. Warmuth. Learnability and the Vapnik–Chervonenkis dimension. Journal of the ACM, 36(4), 929––865, 1989.
[Vapnik(1995)] V. N. Vapnik. The Nature of Statistical Learning Theory. Springer, New York., 1995.
[Wolpert9(1996)] D. H. Wolpert. The lack of a priori distinction between learning algorithms. Neural Computation, 8(7), 1341–1390, 1996.
[McCulloch and Pitts(1943)] W. S. McCulloch and W. Pitts. A logical calculus of ideas immanent in nervous activity. Bulletin of Mathematical Biophysics, 5, 115–133, 1943.
[Rosenblatt(1958)] Frank Rosenblatt. The perceptron. A probabilistic model for information storage and organization in the brain. Psychological Reviews, 65, 386–408, 1958.
[Goodfellow et al.(2016)] I. Goodfellow, Y. Bengio, and A. Courville. Deep Learning. MIT Press, 2016.
[Reynolds(2021)] Anh Reynolds. Understanding convolutional neural networks (cnns). https://anhreynolds.com/blogs/cnn.html, 2021 Accessed: 2024-02-11.
[JurafskyMartin(2023)] Daniel Jurafsky and James H. Martin. Speech and Language Processing. https://web.stanford.edu/ jurafsky/slp3, 2023
[Hochreiter(1991)] S. Hochreiter. Untersuchungen zu dynamischen neuronalen Netzen. Diplom thesis. Diplom thesis, Institut f. Informatik, Technische Univ. Munich., Germany, 1991.
[CARTPennStateCourse(2024)] Penn State’s Department of Statistics. Course notes for STAT 508: Applied Data Mining and Statistical Learning, Lesson 11. https://online.stat.psu.edu/stat508/, 2024 Creative Commons license CC BY-NC 4.0
[Breiman(1996)] Leo Breiman. Bagging predictors. Machine Learning, 24(2), 123–140, 1996. doi:10.1007/BF00058655
[Elman(1990)] J. L. Elman. Finding structure in time. Cognitive science, 14(2), 179–211, 1990.
[Werbos(1974)] P. Werbos. Beyond regression: new tools for prediction and analysis in the behavioral sciences. Ph.D. thesis. Ph.D. thesis, Harvard University, USA, 1974.
[SchusterPaliwal(1997)] M. Schuster and K. K. Paliwal. Bidirectional recurrent neural networks. IEEE Transactions on Signal Processing, 45, 2673–2681, 1997.
[HochreiterSchmidhuber(1997)] S. Hochreiter and J. Schmidhuber. Long short-term memory. Neural Computation, 9(8),1735–1780, 1997.
[Bellman(1957)] Richard Bellman. A Markovian Decision Process. Journal of Mathematics and Mechanics, 6(5):679–684, 1957. http://www.jstor.org/stable/24900506
[Bertsekas(1987)] Dimitri P. Bertsekas. Dynamic Programming: Deterministic and Stochastic Models. Prentice-Hall, 1987.
[LittmanDeanKaelbling(1995)] M. L. Littman, T. L. Dean, and L. P. Kaelbling. On the complexity of solving Markov decision problems. In Proceedings of the Eleventh Annual Conference on Uncertainty in Articial Intelligence (UAI-95), Montreal, Québec, Canada, 1995.
[Li(2018)] Y. Li. Deep reinforcement learning. . https://arxiv.org/abs/1810.06339 arXiv:1810.06339
[Son et al.(2022)] Ki Young Son, Jongwoo Ko, Eunseok Kim, Si Young Lee, Min-Ji Kim, Jisang Han, Eunhae Shin, Tae-Young Chung, and Dong Hui Lim. Deep learningbased cataract detection and grading from slit-lamp and retro-illumination photographs: Model development and validation study.. Ophthalmology Science, 2(2), 2022.