On the need for a right to cognitive privacy

This paper argues that legal privacy should be afforded to the content of the mind, comparing cognitive privacy to other protected forms of privacy and briefly addressing the potential pitfalls of compulsory neuroimaging

Serving deep learning models in a serverless platform

Serverless computing has emerged as a compelling paradigm for the development and deployment of a wide range of event based cloud applications. At the same time, cloud providers and enterprise companies are heavily adopting machine learning and Artificial Intelligence to either differentiate themselves, or provide their customers with value added services. In this work we evaluate the suitability of a serverless computing environment for the inferencing of large neural network models. Our experimental evaluations are executed on the AWS Lambda environment using the MxNet deep learning framework. Our experimental results show that while the inferencing latency can be within an acceptable range, longer delays due to cold starts can skew the latency distribution and hence risk violating more stringent SLAs

Unintegrated gluon distributions for forward jets at LHC

We test several BFKL-like evolution equations for unintegrated gluon distributions against forward-central dijet production at LHC. Our study is based on fitting the evolution scenarios to the LHC data using the high energy factorization approach. Thus, as a by-product, we obtain a set of LHC-motivated unintegrated gluon distributions ready to use. We utilize this application by calculating azimuthal decorrelations for forward-central dijet production and compare with existing data.Comment: 18 pages, 6 figures; small corrections in the text and reference

General Mass Scheme for Jet Production in DIS

We propose a method for calculating DIS jet production cross sections in QCD at NLO accuracy with consistent treatment of heavy quarks. The scheme relies on the dipole subtraction method for jets, which we extend to all possible initial state splittings with heavy partons, so that the Aivazis-Collins-Olness-Tung massive collinear factorization scheme (ACOT) can be applied. As a first check of the formalism we recover the ACOT result for the heavy quark structure function using a dedicated Monte Carlo program.Comment: 6 pages, 2 figure