32-G449 (KIva/Patel)

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Memory-Efficient Adaptive Optimization for Humungous-Scale Learning

32-G449 (KIva/Patel)

Adaptive gradient-based optimizers such as AdaGrad and Adam are among the methods of choice in modern machine learning. These methods maintain second-order statistics of each model parameter, thus doubling the memory footprint of the optimizer. In behemoth-size applications, this memory overhead restricts the size of the model being used as well as the number of…

Using Computer Vision to Study Society: Methods and Challenges

32-G449 (KIva/Patel)

  Abstract: Targeted socio-economic policies require an accurate understanding of a country's demographic makeup. To that end, the United States spends more than 1 billion dollars a year gathering census data such as race, gender, education, occupation and unemployment rates. Compared to the traditional method of collecting surveys across many years which is costly and…


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