See maxout in All languages combined, or Wiktionary
{ "etymology_templates": [ { "args": { "1": "en", "2": "maximum", "3": "dropout" }, "expansion": "Blend of maximum + dropout", "name": "blend" } ], "etymology_text": "Blend of maximum + dropout; coined in a 2013 paper by Ian J. Goodfellow et al.", "head_templates": [ { "args": { "1": "-" }, "expansion": "maxout (uncountable)", "name": "en-noun" } ], "lang": "English", "lang_code": "en", "pos": "noun", "senses": [ { "categories": [ { "kind": "other", "name": "English blends", "parents": [], "source": "w" }, { "kind": "other", "name": "English entries with incorrect language header", "parents": [ "Entries with incorrect language header", "Entry maintenance" ], "source": "w" }, { "kind": "other", "name": "Pages with 1 entry", "parents": [], "source": "w" }, { "kind": "other", "name": "Pages with entries", "parents": [], "source": "w" } ], "examples": [ { "ref": "2016, George Saon, Tom Sercu, Steven Rennie, Hong-Kwang J. Kuo, “The IBM 2016 English Conversational Telephone Speech Recognition System”, in arXiv:", "text": "On the acoustic side, we use a score fusion of three strong models: recurrent nets with maxout activations, very deep convolutional nets with 3x3 kernels, and bidirectional long-short term memory nets which operate on bottleneck features.", "type": "quote" } ], "glosses": [ "A certain approach to neural networks that attempts to improve on the dropout technique. Its activation function is the maximum of the inputs." ], "id": "en-maxout-en-noun-0h00GUEI", "links": [ [ "neural network", "neural network" ], [ "dropout", "dropout" ], [ "activation function", "activation function" ], [ "input", "input" ] ], "related": [ { "word": "dropout" }, { "word": "softmax" } ], "tags": [ "uncountable" ] } ], "word": "maxout" }
{ "etymology_templates": [ { "args": { "1": "en", "2": "maximum", "3": "dropout" }, "expansion": "Blend of maximum + dropout", "name": "blend" } ], "etymology_text": "Blend of maximum + dropout; coined in a 2013 paper by Ian J. Goodfellow et al.", "head_templates": [ { "args": { "1": "-" }, "expansion": "maxout (uncountable)", "name": "en-noun" } ], "lang": "English", "lang_code": "en", "pos": "noun", "related": [ { "word": "dropout" }, { "word": "softmax" } ], "senses": [ { "categories": [ "English blends", "English entries with incorrect language header", "English lemmas", "English nouns", "English terms with quotations", "English uncountable nouns", "Pages with 1 entry", "Pages with entries" ], "examples": [ { "ref": "2016, George Saon, Tom Sercu, Steven Rennie, Hong-Kwang J. Kuo, “The IBM 2016 English Conversational Telephone Speech Recognition System”, in arXiv:", "text": "On the acoustic side, we use a score fusion of three strong models: recurrent nets with maxout activations, very deep convolutional nets with 3x3 kernels, and bidirectional long-short term memory nets which operate on bottleneck features.", "type": "quote" } ], "glosses": [ "A certain approach to neural networks that attempts to improve on the dropout technique. Its activation function is the maximum of the inputs." ], "links": [ [ "neural network", "neural network" ], [ "dropout", "dropout" ], [ "activation function", "activation function" ], [ "input", "input" ] ], "tags": [ "uncountable" ] } ], "word": "maxout" }
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This page is a part of the kaikki.org machine-readable English dictionary. This dictionary is based on structured data extracted on 2024-12-08 from the enwiktionary dump dated 2024-12-04 using wiktextract (bb46d54 and 0c3c9f6). The data shown on this site has been post-processed and various details (e.g., extra categories) removed, some information disambiguated, and additional data merged from other sources. See the raw data download page for the unprocessed wiktextract data.
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