Jun 7, 2019
Continuing in research topics, Andy and Dave discuss research from MIT that treats image classification adversarial examples not as bugs, but as features – and intentionally mislabeled pictures; the approach adds robustness to vulnerability, and provides evidence that adversarial vulnerability is caused by non-robust features and is not inherently tied to the standard training framework. The Bulletin of the Atomic Scientists releases The Global Competition for AI Dominance in its May 2019 issue. Isaac Godfrie provides a summary of “few shot” learning papers that were presented at ICLR 2019. A research paper shows the interface between machine learning and the physical sciences. A new survey from Alegion and Dimensional Research examines the data issues impacting AI/ML research (for example, 96% of companies surveyed said they ran into problem with data quality). Georgios Mastorakis examines issues that arise from taking a human-like approach to training algorithms. Mohri, Rostamizadeh, and Talwalkar release a graduate-level book on Foundations of Machine Learning through MIT Press. CollegeHumor produces “A Computer Co-Wrote this Sketch,” in which the characters appear to become aware of their situation. And finally, the Genetic and Evolutionary Computation Conference is scheduled for 13-17 July 2019 in Prague, Czech Republic.
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