AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper introduces the technique of "persistence of memory" to greatly extend and improve the random subspace methods, and establishes to the knowledge the first theoretical analysis of classical SSD methods for sparse functions.
A statistical approach to bias rectification that can be combined in a turn-key fashion with any classical GZSL feature learner as a blackbox, thereby suggesting a wide scope of applicability of this method for a wide variety of GZSL implementations in different domains.
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