Alpha MAML: Adaptive Model-Agnostic Meta-Learning

Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks. The MAML algorithm performs well on few-shot learning problems in classification, regression, and fine-tuning of policy gradients in reinforcement learning, but comes with the need for costly hyperparameter tuning for training stability. We address this shortcoming by introducing an extension to MAML, called Alpha MAML, to incorporate an online hyperparameter adaptation scheme that eliminates the need to tune meta-learning and learning rates. Our results with the Omniglot database demonstrate a substantial reduction in the need to tune MAML training hyperparameters and improvement to training stability with less sensitivity to hyperparameter choice.Comment: 6th ICML Workshop on Automated Machine Learning (2019

KL Guided Domain Adaptation

Domain adaptation is an important problem and often needed for real-world applications. In this problem, instead of i.i.d. datapoints, we assume that the source (training) data and the target (testing) data have different distributions. With that setting, the empirical risk minimization training procedure often does not perform well, since it does not account for the change in the distribution. A common approach in the domain adaptation literature is to learn a representation of the input that has the same distributions over the source and the target domain. However, these approaches often require additional networks and/or optimizing an adversarial (minimax) objective, which can be very expensive or unstable in practice. To tackle this problem, we first derive a generalization bound for the target loss based on the training loss and the reverse Kullback-Leibler (KL) divergence between the source and the target representation distributions. Based on this bound, we derive an algorithm that minimizes the KL term to obtain a better generalization to the target domain. We show that with a probabilistic representation network, the KL term can be estimated efficiently via minibatch samples without any additional network or a minimax objective. This leads to a theoretically sound alignment method which is also very efficient and stable in practice. Experimental results also suggest that our method outperforms other representation-alignment approaches

Amortized Rejection Sampling in Universal Probabilistic Programming

Existing approaches to amortized inference in probabilistic programs with unbounded loops can produce estimators with infinite variance. An instance of this is importance sampling inference in programs that explicitly include rejection sampling as part of the user-programmed generative procedure. In this paper we develop a new and efficient amortized importance sampling estimator. We prove finite variance of our estimator and empirically demonstrate our method's correctness and efficiency compared to existing alternatives on generative programs containing rejection sampling loops and discuss how to implement our method in a generic probabilistic programming framework

Heart Rate-Corrected QT Interval Helps Predict Mortality after Intentional Organophosphate Poisoning

INTRODUCTION: In this study, we investigated the outcomes for patients with intentional organophosphate poisoning. Previous reports indicate that in contrast to normal heart rate-corrected QT intervals (QTc), QTc prolongation might be indicative of a poor prognosis for patients exposed to organophosphates. METHODS: We analyzed the records of 118 patients who were referred to Chang Gung Memorial Hospital for management of organophosphate poisoning between 2000 and 2011. Patients were grouped according to their initial QTc interval, i.e., normal (<0.44 s) or prolonged (>0.44 s). Demographic, clinical, laboratory, and mortality data were obtained for analysis. RESULTS: The incidence of hypotension in patients with prolonged QTc intervals was higher than that in the patients with normal QTc intervals (P = 0.019). By the end of the study, 18 of 118 (15.2%) patients had died, including 3 of 75 (4.0%) patients with normal QTc intervals and 15 of 43 (34.9%) patients with prolonged QTc intervals. Using multivariate-Cox-regression analysis, we found that hypotension (OR = 10.930, 95% CI = 2.961-40.345, P = 0.000), respiratory failure (OR = 4.867, 95% CI = 1.062-22.301, P = 0.042), coma (OR = 3.482, 95% CI = 1.184-10.238, P = 0.023), and QTc prolongation (OR = 7.459, 95% CI = 2.053-27.099, P = 0.002) were significant risk factors for mortality. Furthermore, it was revealed that non-survivors not only had longer QTc interval (503.00±41.56 versus 432.71±51.21 ms, P = 0.002), but also suffered higher incidences of hypotension (83.3 versus 12.0%, P = 0.000), shortness of breath (64 versus 94.4%, P = 0.010), bronchorrhea (55 versus 94.4%, P = 0.002), bronchospasm (50.0 versus 94.4%, P = 0.000), respiratory failure (94.4 versus 43.0%, P = 0.000) and coma (66.7 versus 11.0%, P = 0.000) than survivors. Finally, Kaplan-Meier analysis demonstrated that cumulative mortality was higher among patients with prolonged QTc intervals than among those with normal QTc intervals (Log-rank test, Chi-square test = 20.36, P<0.001). CONCLUSIONS: QTc interval helps predict mortality after intentional organophosphate poisoning

Оценка эффективности региональных расходов на здравоохранение в России

Life expectancy to healthcare spending ratio differs significantly among the Russian regions. The differences could be explained with both non-discretionary factors and the regional management efficiency. The main aim of this article is to evaluate the efficiency of the regional healthcare in Russia employing the formal methodological approach. We use three-step data envelopment analysis (DEA) in order to (1) calculate the technical efficiency scores for regional healthcare systems, (2) determine non-discretionary factors affecting the scores and (3) exclude the non-discretionary component from scores to asses the management efficiency. Using data for 76 Russian regions in 2006-2013 we found approx. 27% regional healthcare spending inefficient, which equals to real 269-435 billion rubles of inefficient spending annually. Соотношение ожидаемой продолжительности жизни и подушевых расходов на здравоохранение в России существенно различается между субъектами. Такие различия объясняются как действием внешних факторов, так и различиями в эффективности управления здравоохранением. Целью настоящего исследования является разработка и апробация формального подхода к количественной оценке эффективности региональных расходов на здравоохранение в России. Для достижения указанной цели был использован трехступенчатый метод анализа среды функционирования, включающий в себя: 1) оценку соотношений результатов и затрат в здравоохранении; 2) определение влияния внешних факторов; 3) расчет скорректированной оценки эффективности без учета влияния внешних факторов, то есть эффективности, определяемой качеством государственного управления. Для расчетов использовались данные по 76 субъектам РФ за период 2006-2013 гг. В результате было установлено, что в среднем около 27% расходов на здравоохранение в субъектах РФ являются неэффективными. Общая величина неэффективных расходов в 76 субъектах за рассматриваемый период колебалась в реальном выражении от 269 до 435 млрд руб. в год в ценах 2013 г.

Towards a hybrid computational strategy based on Deep Learning for incompressible flows

The Poisson equation is present in very different domains of physics and engineering. In most cases, this equation can not be solved directly and iterative solvers are used. For many solvers, this step is computationally intensive. In this study, an alternative resolution method based on neural networks is evaluated for incompressible flows. A fluid solver coupled with a Convolutional Neural Network is developed and trained on random cases with constant density to predict the pressure field. Its performance is tested in a plume configuration, with different buoyancy forces, parametrized by the Richardson number. The neural network is compared to a traditional Jacobi solver. The performance improvement is considerable, although the accuracy of the network is found to depend on the flow operating point: low errors are obtained at low Richardson numbers, whereas the fluid solver becomes unstable with large errors for large Richardson number. Finally, a hybrid strategy is proposed in order to benefit from the calculation acceleration while ensuring a user-defined accuracy level. In particular, this hybrid CFD-NN strategy, by maintaining the desired accuracy whatever the flow condition, makes the code stable and reliable even at large Richardson numbers for which the network was not trained for. This study demonstrates the capability of the hybrid approach to tackle new flow physics, unseen during the network training

Uluslararası sivil havacılık kuralları ve Türkiye'de uçuş eğitimi organizasyonları

Tez (yüksek lisans) - Anadolu ÜniversitesiAnadolu Üniversitesi, Sosyal Bilimler Enstitüsü, Sivil Havacılık Yönetimi Anabilim DalıKayıt no: 155843Dünyamızın ekonomik, toplumsal ve siyasal görünümün değiştiren bir globalleşme sürecinde bulunuyoruz. Hayatımızın her alanında yaşanan değişim ve gelişme sivil havacılık sektöründe de belirgin bir şekilde görülmektedir. Türkiye olarak Avrupa Birliği'ne girme hazırlıkları yaptığımız şu günlerde, sivil havacılık kurum ve kuruluşlarımızın da Avrupa Havacılık Kuralları'na uygun yapılanması ve operasyon yapması konusundaki çalışmaların sonuna yaklaşmaktayız. Bu amaca yönelik hazırlanmış bu tezin birinci bölümünde, yirminci yüzyılda başlayan ve gelişen sivil havacılığın dünyadaki ve Türkiye'deki gelişimi ile uluslararası ve ulusal havacılık kuruluşları incelenmiştir. İkinci bölümde, uluslararası sivil havacılık kurallarını koyan ve denetleyen ICAO, FAA ve JAA kuruluşları tarafından oluşturulan sivil havacılık eğitim kuralları bulunmaktadır. JAA kuralları, günümüzdeki özelliği dikkate alınarak daha detaylı işlenmiştir. Böylece ülkemizdeki tüm sivil havacılık faaliyetlerinde JAA ve JAR kurallarına uyum çalışmalarına bir katkıda bulunmak amaçlanmıştır. Üçüncü bölümde, Türkiye'deki sivil havacılık eğitim merkezlerinden, karşılıklı görüşme ve anket tekniği kullanılarak elde edilen bilgiler yer almıştır. Son bölümde ise bulgular ve öneriler sunulmuştur

The Argumentative Mediator

In this paper we introduce a negotiation mediator in a multiagent context. When negotiation fails, a mediator can interact with the parties, find out about their goals, ontologies, and arguments for and against negotiation outcome, and suggest solutions based on previous experience. An algorithmic schema to be instantiated with particular argumentation, semantic alignment and case-base reasoning techniques is presented. The proposal is neutral with respect to which particular technique is selected. An example illustrates the approach that is framed in the existing body of literature on argumentation and mediation.This research has been supported by Generalitat de Catalunya project 2014 SGR 118.Peer Reviewe