Kaan Kara — accepted AI-conference papers

2018

Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond

AISTATS 2018poster

For Markov chain Monte Carlo methods, one of the greatest discrepancies between theory and system is the scan order — while most theoretical development on the mixing time analysis deals with random updates, real-world systems are implemented with systematic scans. We bridge this gap for models that…

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2017

ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning

Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang

ICML 2017poster

Recently there has been significant interest in training machine-learning models at low precision: by reducing precision, one can reduce computation and communication by one order of magnitude. We examine training at reduced precision, both from a theoretical and practical perspective, and ask: is i…

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