Dropout Training as Adaptive Regularization

Dropout and other feature noising schemes control overfitting by artificially corrupting the training data. For generalized linear models, dropout performs a form of adaptive regularization. Using this viewpoint, we show that the dropout regularizer is first-order equivalent to an L2 regularizer applied after scaling the features by an estimate of the inverse diagonal Fisher information matrix. We also establish a connection to AdaGrad, an online learning algorithm, and find that a close relative of AdaGrad operates by repeatedly solving linear dropout-regularized problems. By casting dropout as regularization, we develop a natural semi-supervised algorithm that uses unlabeled data to create a better adaptive regularizer. We apply this idea to document classification tasks, and show that it consistently boosts the performance of dropout training, improving on state-of-the-art results on the IMDB reviews dataset.Comment: 11 pages. Advances in Neural Information Processing Systems (NIPS), 201

Hexapod Coloron at the LHC

Instead of the usual dijet decay, the coloron may mainly decay into its own "Higgs bosons", which subsequently decay into many jets. This is a general feature of the renormalizable coloron model, where the corresponding "Higgs bosons" are a color-octet $\Theta$ and a color-singlet $\phi_I$. In this paper, we perform a detailed collider study for the signature of $pp \rightarrow G' \rightarrow (\Theta \rightarrow gg) (\phi_I \rightarrow gg q\bar{q})$ with the coloron $G'$ as a six-jet resonance. For a light $\phi_I$ below around 0.5 TeV, it may be boosted and behave as a four-prong fat jet. We also develop a jet-substructure-based search strategy to cover this boosted $\phi_I$ case. Independent of whether $\phi_I$ is boosted or not, the 13 TeV LHC with 100 fb$^{-1}$ has great discovery potential for a coloron with the mass sensitivity up to 5 TeV.Comment: 18 pages, 10 figure

Review of Sida\u27s Support to Mine Action 2001-2009 - Final Report

This report presents the findings, conclusions and recommendations of an external review of Sida\u27s support to mine action activities between 2001 and 2009 undertaken by COWI A/S and Channel Research. The review provides an overview of Sida\u27s engagement in mine action during the decade, as well as assessments of the relevance of relevant Sida policies and strategies, and the results achieved through support to global organisations and country level programmes. The review included country field visits to Sida supported mine action programmes in Iraq and the Democratic Republic of Congo. The methodology applied was based on the evaluation frameworks of OECD\u27s Development Assistance Committee and Sida, focussing on relevance, effectiveness, efficiency, sustainability and impact, as well as the IMAS Guidelines for Evaluation of Mine Action

Performance trials on different rates and ratios of N and P fertilisation in Ethiopia to inform field-specific Maize-Nutrient-Management advisory

This report of the Scaling Readiness of Nutrient Management decision Support Tools project focuses on agronomic trials that serve to inform the development of scalable, field-specific advisory for maize farmers in Ethiopia. These trials were conducted to generate additional information required to make a mobile phone-based nutrient decision support tool – Maize-Nutrient-Manager – more scalable in the context of institutional limitations in fertilizer availability and distribution in Ethiopia. The focus of the trials is on establishing proper N:P ratio’s for different fertilization rates with the fertilizers available to farmers in West-Shewa and Jimma (two major maize belts in Ethiopia). The trials were conducted with additional funding from the TAMASA project and in collaboration with EIAR. As the latter institute is involved in conducting fertilizer trials and the development of recommendations, this collaboration also aimed at forming an appropriate entry point for institutionalization of the decision support tool that is being developed