Narrowing the Gap: Random Forests In Theory and In Practice

Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two ways. We present a new theoretically tractable variant of random regression forests and prove that our algorithm is consistent. We also provide an empirical evaluation, comparing our algorithm and other theoretically tractable random forest models to the random forest algorithm used in practice. Our experiments provide insight into the relative importance of different simplifications that theoreticians have made to obtain tractable models for analysis.Comment: Under review by the International Conference on Machine Learning (ICML) 201

An Approach to Email Classification Using Bayesian Theorem

Email Classifiers based on Bayesian theorem have been very effective in Spam filtering due to their strong categorization ability and high precision. This paper proposes an algorithm for email classification based on Bayesian theorem. The purpose is to automatically classify mails into predefined categories. The algorithm assigns an incoming mail to its appropriate category by checking its textual contents. The experimental results depict that the proposed algorithm is reasonable and effective method for email classification

Linear and Parallel Learning of Markov Random Fields

We introduce a new embarrassingly parallel parameter learning algorithm for Markov random fields with untied parameters which is efficient for a large class of practical models. Our algorithm parallelizes naturally over cliques and, for graphs of bounded degree, its complexity is linear in the number of cliques. Unlike its competitors, our algorithm is fully parallel and for log-linear models it is also data efficient, requiring only the local sufficient statistics of the data to estimate parameters

Co-simulation of Continuous Systems: A Tutorial

Co-simulation consists of the theory and techniques to enable global simulation of a coupled system via the composition of simulators. Despite the large number of applications and growing interest in the challenges, the field remains fragmented into multiple application domains, with limited sharing of knowledge. This tutorial aims at introducing co-simulation of continuous systems, targeted at researchers new to the field

Distributed Parameter Estimation in Probabilistic Graphical Models

This paper presents foundational theoretical results on distributed parameter estimation for undirected probabilistic graphical models. It introduces a general condition on composite likelihood decompositions of these models which guarantees the global consistency of distributed estimators, provided the local estimators are consistent

Analisis Zakat sebagai Instrument Kebijakan Fiskal pada Masa Khalifah Umar Bin Khattab R. A

Penelitian ini menjelaskan secara garis besar dan deskriftif zakat sebagai instrumen kebijakan fiskal pada masa khaliffah ummar bim khattab dengan strategi dan pengalokasiannya. Zakat memiliki peran penting dalam pertumbuhan dan kebijakan fikal pada masa awal islam khusunya masa khalifah umar bin khattab. Disamping sebagai sumber pendapatan negara, zaka juga mampu menunjang pengeluaran negara baik dalam bentuk government expenditure (pengeluaran belanja negara) maupun government transfer (pengeluaran transfer). Zakat juga berperan penting dalam arus perekonomian pemerintahan islam saat itu, terutama untuk menciptakan kesejahteraan massyarakat dan keamanan terutama golongan lemah yang tidak banyak memiliki sumberdaya. Sebeb, dikarenakan zakat merupakan sumber pendapatan negara yang takan pernah habis dan kering saat itu