Google Vizier: A Service for Black-Box Optimization Daniel Golovin, Benjamin Solnik, Subhodeep Moitra, Greg Kochanski, John Karro, D. Sculley {dgg, bsolnik, smoitra, gpk, karro, dsculley}@google.com Google Research Pittsburgh, PA, USA ABSTRACT Any sufficiently complex system acts as a black box when it becomes easier to experiment with than to understand. Hence, black-box optimization has become i
Secrets, Lies, and Account Recovery: Lessons from the Use of Personal Knowledge Questions at Google Joseph Bonneau ∗ Stanford University & EFF jbonneau@cs.stanford.edu Elie Bursztein Google elieb@google.com Ilan Caron Google ilanc@google.com Rob Jackson Google roj@google.com Mike Williamson Google miwilliamson@google.com ABSTRACT We examine the first large real-world data set on personal knowl- ed
A sound vocabulary and datasetAudioSet consists of an expanding ontology of 632 audio event classes and a collection of 2,084,320 human-labeled 10-second sound clips drawn from YouTube videos. The ontology is specified as a hierarchical graph of event categories, covering a wide range of human and animal sounds, musical instruments and genres, and common everyday environmental sounds. By releasing
A sound vocabulary and datasetAudioSet consists of an expanding ontology of 632 audio event classes and a collection of 2,084,320 human-labeled 10-second sound clips drawn from YouTube videos. The ontology is specified as a hierarchical graph of event categories, covering a wide range of human and animal sounds, musical instruments and genres, and common everyday environmental sounds. By releasing
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