Ati Technologies Ulc

Advanced Micro Devices Corporation

Max Kiehn

Nicholas P Malaya

Stanislav Ivashkevich

A technique for generating a trained discriminator is provided. The technique includes applying one or more of a glitched image or an unglitched image to a discriminator; receiving classification output from the discriminator; adjusting weights of the discriminator to improve classification accuracy of the discriminator; applying noise to a generator; receiving an output image from the generator; applying the output image to the discriminator to obtain a classification; and adjusting weights of one of the discriminator or the generator to improve ability of the generator to reduce classification accuracy of the discriminator, based on the classification.

Automated artifact detection

A technique for detecting a glitch in an image is provided. The technique includes providing an image to a plurality of individual classifiers to generate a plurality of individual classifier outputs and providing the plurality of individual classifier outputs to an ensemble classifier to generate a glitch classification.

Described herein are methods and related apparatus for the allocation of computing resources to perform computing tasks. The methods described herein may be used to allocate computing tasks to many different types of computing resources, such as processor cores, individual computers, and virtual machines. Characteristics of the available computing resources, as well as other aspects of the computing environment, are modeled in a multidimensional coordinate system. Each coordinate point in the coordinate system corresponds to a unique combination of attributes of the computing resources/computing environment, and each coordinate point is associated with a weight that indicates the relative desirability of the coordinate point. To allocate a computing resource to execute a task, the weights of the coordinate points, as well as other related factors, are analyzed.

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Markham, Canada

Max Kiehn