{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T05:20:55Z","timestamp":1755926455942,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":6,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,3,21]],"date-time":"2020-03-21T00:00:00Z","timestamp":1584748800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100014718","name":"National Science Foundation","doi-asserted-by":"publisher","award":["HRD-1242122"],"award-info":[{"award-number":["HRD-1242122"]}],"id":[{"id":"10.13039\/100014718","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,3,21]]},"DOI":"10.1145\/3396474.3396481","type":"proceedings-article","created":{"date-parts":[[2020,5,30]],"date-time":"2020-05-30T12:35:11Z","timestamp":1590842111000},"page":"30-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Deep Learning (Partly) Demystified"],"prefix":"10.1145","author":[{"given":"Vladik","family":"Kreinovich","sequence":"first","affiliation":[{"name":"The University of Texas at El Paso"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga","family":"Kosheleva","sequence":"additional","affiliation":[{"name":"The University of Texas at El Paso"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,5,30]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"1","volume-title":"Constraint Programming and Decision Making: Theory and Applications","author":"Baral C.","year":"2018","unstructured":"C. Baral , O. Fuentes , and V. Kreinovich , \" Why deep neural networks: a possible theoretical explanation \", In: M. Ceberio and V. Kreinovich (eds.), Constraint Programming and Decision Making: Theory and Applications , Springer Verlag , Berlin, Heidelberg , 2018 , pp. 1 -- 6 . C. Baral, O. Fuentes, and V. Kreinovich, \"Why deep neural networks: a possible theoretical explanation\", In: M. Ceberio and V. Kreinovich (eds.), Constraint Programming and Decision Making: Theory and Applications, Springer Verlag, Berlin, Heidelberg, 2018, pp. 1--6."},{"key":"e_1_3_2_1_2_1","volume-title":"Pattern Recognition and Machine Learning","author":"Bishop C. M.","year":"2006","unstructured":"C. M. Bishop , Pattern Recognition and Machine Learning , Springer , New York , 2006 . C. M. Bishop, Pattern Recognition and Machine Learning, Springer, New York, 2006."},{"key":"e_1_3_2_1_3_1","volume-title":"Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications","author":"Fuentes O.","year":"2019","unstructured":"O. Fuentes , J. Parra , E. Anthony , and V. Kreinovich , \" Why rectified linear neurons are efficient: a possible theoretical explanations \", In: O. Kosheleva, S. Shary, G. Xiang, and R. Zapatrin (eds.), Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications , Springer , Cham, Switzerland , 2019 , to appear. O. Fuentes, J. Parra, E. Anthony, and V. Kreinovich, \"Why rectified linear neurons are efficient: a possible theoretical explanations\", In: O. Kosheleva, S. Shary, G. Xiang, and R. Zapatrin (eds.), Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications, Springer, Cham, Switzerland, 2019, to appear."},{"key":"e_1_3_2_1_4_1","first-page":"15","volume-title":"Smart Unconventional\/Modelling","author":"Gholamy A.","year":"2019","unstructured":"A. Gholamy , J. Parra , V. Kreinovich , O. Fuentes , and E. Anthony , \" How to best apply deep neural networks in geosciences: towards optimal 'averaging' in dropout training \", In: J. Watada, Shing Chieng Tan, P. Vasant, E. Padmanabhan, and L. C. Jain (eds.), Smart Unconventional\/Modelling , Simulation and Optimization for Geosciences and Petroleum Engineering, Springer Verlag , 2019 , pp. 15 -- 26 . A. Gholamy, J. Parra, V. Kreinovich, O. Fuentes, and E. Anthony, \"How to best apply deep neural networks in geosciences: towards optimal 'averaging' in dropout training\", In: J. Watada, Shing Chieng Tan, P. Vasant, E. Padmanabhan, and L. C. Jain (eds.), Smart Unconventional\/Modelling, Simulation and Optimization for Geosciences and Petroleum Engineering, Springer Verlag, 2019, pp. 15--26."},{"key":"e_1_3_2_1_5_1","volume-title":"Deep Leaning","author":"Goodfellow I.","year":"2016","unstructured":"I. Goodfellow , Y. Bengio , and A. Courville , Deep Leaning , MIT Press , Cambridge, Massachusetts , 2016 . I. Goodfellow, Y. Bengio, and A. Courville, Deep Leaning, MIT Press, Cambridge, Massachusetts, 2016."},{"key":"e_1_3_2_1_6_1","volume-title":"S. N. Shahbazova, J. Kacprzyk, V. E. Balas, and V. Kreinovich (eds.) Proceedings of the World Conference on Soft Computing","author":"Kreinovich V.","year":"2018","unstructured":"V. Kreinovich , \"From traditional neural networks to deep learning : towards mathematical foundations of empirical successes \", In: S. N. Shahbazova, J. Kacprzyk, V. E. Balas, and V. Kreinovich (eds.) Proceedings of the World Conference on Soft Computing , Baku, Azerbaijan , May 29-31, 2018 . V. Kreinovich, \"From traditional neural networks to deep learning: towards mathematical foundations of empirical successes\", In: S. N. Shahbazova, J. Kacprzyk, V. E. Balas, and V. Kreinovich (eds.) Proceedings of the World Conference on Soft Computing, Baku, Azerbaijan, May 29-31, 2018."}],"event":{"name":"ISMSI '20: 2020 4th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence","sponsor":["University of Delhi"],"location":"Thimphu Bhutan","acronym":"ISMSI '20"},"container-title":["Proceedings of the 2020 4th International Conference on Intelligent Systems, Metaheuristics &amp; Swarm Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3396474.3396481","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3396474.3396481","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:38:46Z","timestamp":1750199926000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3396474.3396481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,21]]},"references-count":6,"alternative-id":["10.1145\/3396474.3396481","10.1145\/3396474"],"URL":"https:\/\/doi.org\/10.1145\/3396474.3396481","relation":{},"subject":[],"published":{"date-parts":[[2020,3,21]]},"assertion":[{"value":"2020-05-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}