Row 36191

Row ID: 36191 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 36191 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

It depends on what kind of assumptions you make and how strongly you enforce them. There are a number of algorithms and techniques that can be utilized for the desired outcome.

If you wish to assume that each modality (view) is independent from another then you aren't interested in a shared space but rather in a set of spaces, one per view, such that some amount of scatter/class/distance information is retained, while lowering the dimension of the space. Of course, if you want these spaces to interact with one another then you'd have to ponder as to how these features differ or are similar and how to essentially transfer information from one space to the other.

FieldValue
text It depends on what kind of assumptions you make and how strongly you enforce them. There are a number of algorithms and techniques that can be utilized for the desired outcome. If you wish to assume that each modality (view) is independent from another then you aren't interested in a shared space but rather in a set of spaces, one per view, such that some amount of scatter/class/distance information is retained, while lowering the dimension of the space. Of course, if you want these spaces to i…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-21
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url_encoded Z0FBQUFBQm5Lak9ZNmJKa1k4ZWVNZnE4R1BkU3VndFBzaFpKQktqWGZkNS1kTWFUVFZGS2xoekFHR2dkNFVtQW5Yb09aNC1Uak5Gek9BeGJoRDlEUThFVS10ZjVOeWpwdWFxTFpZZ0lCVVhxZ3AwYkh1OXQ1dkhveDJPZC04OVdoa2RjcDIwSFhuWS1sbWR0N1g0dWlncDFQOHhnc09HWGRWTkFSaUU2aEhrM0ZFUDBhbnFOYlpQYzROSzYzN0R2ZWljaWtFVGJzTXNURXRzY2x4VzhPWkxBeGpTVzJSMk5fUT09

Raw Record

{
  "text": "It depends on what kind of assumptions you make and how strongly you enforce them. There are a number of algorithms and techniques that can be utilized for the desired outcome.\n\nIf you wish to assume that each modality (view) is independent from another then you aren't interested in a shared space but rather in a set of spaces, one per view, such that some amount of scatter/class/distance information is retained, while lowering the dimension of the space. Of course, if you want these spaces to interact with one another then you'd have to ponder as to how these features differ or are similar and how to essentially transfer information from one space to the other.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-21",
  "username_encoded": "Z0FBQUFBQm5Lak1KMFVQSFZ0eGI0OURGS3Vrcy1Xc0xubFZxOE1CTmdYbDJNeTdGcUFPVlpjTXdWcWhDZkZGSFEwTnlRb21mTHBvNFZva0JqYWRwQlNYVVFsVWlKQ2pmTmc9PQ==",
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}
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