• Facets (new session)
• Description
• Metadata
• Settings
  • Rule: ActivityStreamsMapasEquivalentb3sb3sifpdbprdf-labelfacetshttp://dbpedia.org/resource/inference/rules/dbpedia#http://dbpedia.org/resource/inference/rules/opencyc#http://dbpedia.org/resource/inference/rules/umbel#http://dbpedia.org/resource/inference/rules/yago#http://dbpedia.org/schema/property_rules#http://www.ontologyportal.org/inference/rules/SUMO#http://www.ontologyportal.org/inference/rules/WordNet#http://www.w3.org/2002/07/owl#ldpoplwebskos-transurn:det:rdf:labelvirtrdf-labelvirtrdf-urlNone
    
  • Inverse Functional Properties: Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects
  • "Same As": Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects (recommended) Apply to subjects, objects and predicates (not recommended on big datasets) Apply to predicates only (special use cases only)

About: CLEVER score     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : dbpedia.org associated with source document(s)

The CLEVER (Cross Lipschitz Extreme Value for nEtwork Robustness) score is a way of measuring the robustness of an artificial neural network towards adversarial attacks.It was developed by a team at the in IBM Research and first presented at the 2018 International Conference on Learning Representations. It was mentioned and reviewed by Ian Goodfellow as well. It was adopted into a educational game Fool The Bank by Narendra Nath Joshi, Abhishek Bhandwaldar and Casey Dugan