Control Over Work Hours and Alternative Work Schedules

[Excerpt] Alternative work schedules encompass work hours that do not necessarily fall inside the perimeters of the traditional and often rigid 8-hour workday or 40-hour workweek. Such schedules allow working people to earn a paycheck while having the flexibility to take care of children, older relatives and other needs. Examples of such schedules include: limits on mandatory overtime, flexible work day, compressed workweek, shift swap and telecommuting. Changes in the workforce and the economy are making alternative work schedules increasingly important for working families trying to balance jobs and family responsibilities

Families Matter: Multigenerational Families in a Volatile Economy

Presents survey findings about factors in the rise in multigenerational families, including job loss and healthcare costs; financial, educational, and other results; and impact on family relationships. Suggests policy options for supporting such families

Degree-doubling graph families

Let G be a family of n-vertex graphs of uniform degree 2 with the property that the union of any two member graphs has degree four. We determine the leading term in the asymptotics of the largest cardinality of such a family. Several analogous problems are discussed.Comment: 9 page

Deep Exponential Families

We describe \textit{deep exponential families} (DEFs), a class of latent variable models that are inspired by the hidden structures used in deep neural networks. DEFs capture a hierarchy of dependencies between latent variables, and are easily generalized to many settings through exponential families. We perform inference using recent "black box" variational inference techniques. We then evaluate various DEFs on text and combine multiple DEFs into a model for pairwise recommendation data. In an extensive study, we show that going beyond one layer improves predictions for DEFs. We demonstrate that DEFs find interesting exploratory structure in large data sets, and give better predictive performance than state-of-the-art models