A principled approach to network neutrality

The issue of regulation for mandated network neutrality is currently live in both the United States and the European Union. Traditionally the models applied have been of the command and control or market regulation variety. Both approaches have been extensively criticised and both have suffered setbacks in recent years. This paper suggests it is time to abandon our experiments with traditional business regulation models and move to a principled approach for network neutrality. This principled approach based upon the rights to privacy, expression and freedom to carry on a business identifies the Internet as a public good which requires to be protected from interference if we are to fully realise its democratic potential. The proposed principled, or rights-based, approach to net neutrality would see regulations for network neutrality based in principles of fundamental rights and not business or market regulation principles. We believe this would be a radical new model for network neutrality regulation

Shrinkage Estimators in Online Experiments

We develop and analyze empirical Bayes Stein-type estimators for use in the estimation of causal effects in large-scale online experiments. While online experiments are generally thought to be distinguished by their large sample size, we focus on the multiplicity of treatment groups. The typical analysis practice is to use simple differences-in-means (perhaps with covariate adjustment) as if all treatment arms were independent. In this work we develop consistent, small bias, shrinkage estimators for this setting. In addition to achieving lower mean squared error these estimators retain important frequentist properties such as coverage under most reasonable scenarios. Modern sequential methods of experimentation and optimization such as multi-armed bandit optimization (where treatment allocations adapt over time to prior responses) benefit from the use of our shrinkage estimators. Exploration under empirical Bayes focuses more efficiently on near-optimal arms, improving the resulting decisions made under uncertainty. We demonstrate these properties by examining seventeen large-scale experiments conducted on Facebook from April to June 2017

Functional Sequential Treatment Allocation

Consider a setting in which a policy maker assigns subjects to treatments, observing each outcome before the next subject arrives. Initially, it is unknown which treatment is best, but the sequential nature of the problem permits learning about the effectiveness of the treatments. While the multi-armed-bandit literature has shed much light on the situation when the policy maker compares the effectiveness of the treatments through their mean, much less is known about other targets. This is restrictive, because a cautious decision maker may prefer to target a robust location measure such as a quantile or a trimmed mean. Furthermore, socio-economic decision making often requires targeting purpose specific characteristics of the outcome distribution, such as its inherent degree of inequality, welfare or poverty. In the present paper we introduce and study sequential learning algorithms when the distributional characteristic of interest is a general functional of the outcome distribution. Minimax expected regret optimality results are obtained within the subclass of explore-then-commit policies, and for the unrestricted class of all policies

Malaria, Production and Income of the Producers of Coffee and Cocoa: an Analysis from Survey Data in Côte d'Ivoire. Malaria, coffee and cocoa production and income

The sectors of coffee and cocoa represented in Côte d'Ivoire, before the political crisis, approximately 15% of the GDP and 40% of exports. The zones of production of these two cultures are in the forest area which is infected with malaria. The culture of these products is less constraining than that of the food crops such as rice or yam (one does not need to replant each year for example). However, the maintenance of the ground and of the trees and pest management contribute to obtain high yields. In addition, these products allow the producers to obtain monetary income. However, output is not the sole determinant of the level of income: precocity and speed of gathering, by permitting early sale, contribute to get higher income. In addition, food crops such as rice growing, are produced in the area. The objective of this paper is twofold, first, to evaluate the role of malaria on coffee and cocoa productions, second, to assess if the behaviour of rural households facing a liberalisation of the coffee and cocoa chains has an impact on their income. Three functions are thus estimated: production of coffee, production of cocoa and income. Data are taken from a survey carried out on 800 households (21 villages) in 1999 in the forest area of Danané. The main results are the absence of malaria impact on productions and the dominance of individual over collective sale strategies

An efficient algorithm for learning with semi-bandit feedback

We consider the problem of online combinatorial optimization under semi-bandit feedback. The goal of the learner is to sequentially select its actions from a combinatorial decision set so as to minimize its cumulative loss. We propose a learning algorithm for this problem based on combining the Follow-the-Perturbed-Leader (FPL) prediction method with a novel loss estimation procedure called Geometric Resampling (GR). Contrary to previous solutions, the resulting algorithm can be efficiently implemented for any decision set where efficient offline combinatorial optimization is possible at all. Assuming that the elements of the decision set can be described with d-dimensional binary vectors with at most m non-zero entries, we show that the expected regret of our algorithm after T rounds is O(m sqrt(dT log d)). As a side result, we also improve the best known regret bounds for FPL in the full information setting to O(m^(3/2) sqrt(T log d)), gaining a factor of sqrt(d/m) over previous bounds for this algorithm.Comment: submitted to ALT 201

Gain properties of dye-doped polymer thin films

Hybrid pumping appears as a promising compromise in order to reach the much coveted goal of an electrically pumped organic laser. In such configuration the organic material is optically pumped by an electrically pumped inorganic device on chip. This engineering solution requires therefore an optimization of the organic gain medium under optical pumping. Here, we report a detailed study of the gain features of dye-doped polymer thin films. In particular we introduce the gain efficiency $K$, in order to facilitate comparison between different materials and experimental conditions. The gain efficiency was measured with various setups (pump-probe amplification, variable stripe length method, laser thresholds) in order to study several factors which modify the actual gain of a layer, namely the confinement factor, the pump polarization, the molecular anisotropy, and the re-absorption. For instance, for a 600 nm thick 5 wt\% DCM doped PMMA layer, the different experimental approaches give a consistent value $K\simeq$ 80 cm.MW$^{-1}$. On the contrary, the usual model predicting the gain from the characteristics of the material leads to an overestimation by two orders of magnitude, which raises a serious problem in the design of actual devices. In this context, we demonstrate the feasibility to infer the gain efficiency from the laser threshold of well-calibrated devices. Besides, temporal measurements at the picosecond scale were carried out to support the analysis.Comment: 15 pages, 17 figure

PAC-Bayesian Bounds for Randomized Empirical Risk Minimizers

The aim of this paper is to generalize the PAC-Bayesian theorems proved by Catoni in the classification setting to more general problems of statistical inference. We show how to control the deviations of the risk of randomized estimators. A particular attention is paid to randomized estimators drawn in a small neighborhood of classical estimators, whose study leads to control the risk of the latter. These results allow to bound the risk of very general estimation procedures, as well as to perform model selection

Inland valley rice production systems and malaria infection and disease in the forest region of western Côte d'Ivoire

Background: This study aimed to determine the epidemiological impact of rice cultivation in inland valleys on malaria in the forest region of western Côte d'Ivoire. The importance of malaria was compared in terms of prevalence and parasite density of infections and also in terms of clinical malaria incidence between three agro-ecosystems: (i) uncultivated inland valleys, (R0), (ii) inland valleys with one annual rice cultivation in the rainy season, (R1) and (iii) developed inland valleys with two annual rice cultivation cycles, (R2). Methods: Between May 1998 and March 1999, seven villages of each agro-ecosystem (R0, R1 and R2) were randomly selected among villages pooled by farming system. In these 21 villages, a total of 1,900 people of all age groups were randomly selected and clinically monitored during one year. Clinical and parasitological information was obtained by active case detection of malaria episodes carried out during eight periods of five consecutive days scheduled at six weekly intervals and by cross-sectional surveys. Results: Plasmodium falciparum was the principal parasite observed in the three agro-ecosystems. A level of holoendemicity of malaria was observed in the three agro-ecosystems with more than 75% of children less than 12 months old infected. Geometric mean parasite density in asymptomatic persons varied between 180 and 206 P. falciparum asexual forms per μL of blood and was associated with season and with age, but not with farming system. The mean annual malaria incidence rate reached 0.7 (95% IC 0.5-0.9) malaria episodes per person in R0, 0.7 (95% IC 0.6-0.9) in R1 and 0.6 (95% IC 0.5-0.7) in R2. The burden of malaria was the highest among children under two years of age, with at least four attacks by person-year. Then malaria incidence decreased by half in the two to four-year age group. From the age of five years, the incidence was lower than one attack by person-year. Malaria incidence varied with season with more cases in the rainy season than in the dry season but not with farming system. Conclusion: In the forest area of western Côte d'Ivoire, inland valley rice cultivation was not significantly associated with malaria burden

An insight into polarization states of solid-state organic lasers

The polarization states of lasers are crucial issues both for practical applications and fundamental research. In general, they depend in a combined manner on the properties of the gain material and on the structure of the electromagnetic modes. In this paper, we address this issue in the case of solid-state organic lasers, a technology which enables to vary independently gain and mode properties. Different kinds of resonators are investigated: in-plane micro-resonators with Fabry-Perot, square, pentagon, stadium, disk, and kite shapes, and external vertical resonators. The degree of polarization P is measured in each case. It is shown that although TE modes prevail generally (P>0), kite-shaped micro-laser generates negative values for P, i.e. a flip of the dominant polarization which becomes mostly TM polarized. We at last investigated two degrees of freedom that are available to tailor the polarization of organic lasers, in addition to the pump polarization and the resonator geometry: upon using resonant energy transfer (RET) or upon pumping the laser dye to an higher excited state. We then demonstrate that significantly lower P factors can be obtained.Comment: 12 pages, 12 figure