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We show that a short-term (31-day) reading program, designed to provide age-appropriate reading material, to train teachers in their use, and to support teachers’ initial efforts for about a month, im...
This study presents credible estimates for the causal effect of BMI growth on employment among the obese. By exploring random assignment of a weight-loss intervention based on monetary rewards, I prov...
Using data from a well- executed randomized experiment, we fi nd that the average classroom peer achievement adversely infl uences own student achievement in math and reading in primar...
Arandomized controlled clinical trial is the best way to minimize bias in ascertaining treatment effects, but the credibility of the results of a trial depends on the validity of the methods used to a...
We study the distributed averaging problem on an arbitrary network with a gossip constraint, which means that no node communicates with more than one neighbour in every time slot. We consider algorith...
When evaluating the efficacy of social programs and medical treatments using randomized experiments, the estimated overall average causal effect alone is often of limited value and the researchers mus...
In this paper we analyze the randomized block-coordinate descent (RBCD) methods proposed in [8,11] for minimizing the sum of a smooth convex function and a block-separable convex function. In particul...
In some socio-economic surveys, data are collected on sensitive or stigmatizing issues such as tax evasion, criminal conviction, drug use, etc. In such surveys, direct questioning of respondents is no...
Background: Recent studies have shown a decrease in annualised relapse rates (ARRs) in placebo groups of randomised controlled trials (RCTs) in relapsing multiple sclerosis (RMS). Methods: We conduc...
In this paper we develop a randomized block-coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth block-separable convex function and prove that it obtains an $\epsilon$-...
Most online algorithms used in machine learning today are based on variants of mirror descent or follow-the-leader.
We propose a novel probabilistic method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algorithm that allows to detect obje...
Due to the well-known fact that market returns are not normally distributed, we use generalized hyperbolic distributions for pricing options in a randomized discrete-time setup. The obtained formul...
An Improved Estimation Procedure for Estimating the Proportion of a Population Possessing Sensitive Attribute in Unrelated Question Randomized Response Technique。

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