Four short links: 31 October 2016

Faking Neural Nets, Watson Fintech, Changing Behaviors, and Time-Series Features

By Nat Torkington
October 31, 2016
  1. Universal Adversarial Perturbations — generating images that neural nets will mistakenly classify, and the system generalizes well across universal neural nets.
  2. RegTech — IBM applying Watson to regulations.
  3. Learn faster. Dig deeper. See farther.

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  4. Knowledge-based Interventions are More Likely to Reduce Legal Disparities than are Implicit Bias Interventions — argues that trying to educate about implicit bias doesn’t change outcomes; instead, we should change people’s knowledge about how the structure of the social environment makes them complicit in the perpetuation of bias. Not sure how this will fare in today’s individualistic world, where we aren’t allowed to acknowledge that we operate in a cultural system of largely unspoken and completely arbitrary expectations, values, and other mutually constructed fictions. “Don’t teach THAT controversy!” (via Patrick Forscher)
  5. TSFRESHAutomatic extraction of relevant features from time series.
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