"maxout" meaning in All languages combined

{
  "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"
        }
      ],
      "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": "quotation"
        }
      ],
      "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"
      ],
      "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": "quotation"
        }
      ],
      "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"
}