Multidimensional Poverty: Measurement, Estimation, and Inference

Multidimensional poverty measures give rise to a host of statistical hypotheses which are of interest to applied economists and policy-makers alike. In the specific context of the generalized Alkire-Foster (Alkire and Foster 2008) class of measures, we show that many of these hypotheses can be treated in a unified manner and also tested simultaneously using the minimum p-value methodology of Bennett (2010). When applied to study the relative state of poverty among Hindus and Muslims in India, these tests reveal novel insights into the plight of the poor which are not otherwise captured by traditional univariate approaches.

Spatio-temporal Learning with Arrays of Analog Nanosynapses

Emerging nanodevices such as resistive memories are being considered for hardware realizations of a variety of artificial neural networks (ANNs), including highly promising online variants of the learning approaches known as reservoir computing (RC) and the extreme learning machine (ELM). We propose an RC/ELM inspired learning system built with nanosynapses that performs both on-chip projection and regression operations. To address time-dynamic tasks, the hidden neurons of our system perform spatio-temporal integration and can be further enhanced with variable sampling or multiple activation windows. We detail the system and show its use in conjunction with a highly analog nanosynapse device on a standard task with intrinsic timing dynamics- the TI-46 battery of spoken digits. The system achieves nearly perfect (99%) accuracy at sufficient hidden layer size, which compares favorably with software results. In addition, the model is extended to a larger dataset, the MNIST database of handwritten digits. By translating the database into the time domain and using variable integration windows, up to 95% classification accuracy is achieved. In addition to an intrinsically low-power programming style, the proposed architecture learns very quickly and can easily be converted into a spiking system with negligible loss in performance- all features that confer significant energy efficiency.Comment: 6 pages, 3 figures. Presented at 2017 IEEE/ACM Symposium on Nanoscale architectures (NANOARCH