Search results for "Benchmark"
showing 10 items of 310 documents
An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling
2017
The goal of modeling sentences is to accurately represent their meaning for different tasks. A variety of deep learning architectures have been proposed to model sentences, however, little is known about their comparative performance on a common ground, across a variety of datasets, and on the same level of optimization. In this paper, we provide such a novel comparison for two popular architectures, Recursive Neural Tensor Networks (RNTNs) and Convolutional Neural Networks (CNNs). Although RNTNs have been shown to work well in many cases, they require intensive manual labeling due to the vanishing gradient problem. To enable an extensive comparison of the two architectures, this paper empl…
Sustainable Development Model of EU Cities Compliant with UN Settings
2021
Nowadays, the globally accepted UN concept of sustainable development (SD) is gradu®ally transferred to the city level, including small and medium-sized cities. The implementation of SD settings requires regular measurement of developmental progress to monitor the level achieved in statics and dynamics, and to make strategic decisions for the next period. The existing urban SD indicator systems and indices are not well-suited for the monitoring of specific cities. Benchmarking algorithms and mathematical modelling procedures were applied to create a methodology and mathematical model for measuring the achieved urban SD level and to ensure the most objective selection and proportions of key …
Influence of Quality Filtering Approaches in BEC SMOS L3 Soil Moisture Products
2019
2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2019), 28 July - 2 August 2019, Yokohama, Japan
Parallel Calculation of CCSDT and Mk-MRCCSDT Energies.
2010
A scheme for the parallel calculation of energies at the coupled-cluster singles, doubles, and triples (CCSDT) level of theory, several approximate iterative CCSDT schemes (CCSDT-1a, CCSDT-1b, CCSDT-2, CCSDT-3, and CC3), and for the state-specific multireference coupled-cluster ansatz suggested by Mukherjee with a full treatment of triple excitations (Mk-MRCCSDT) is presented. The proposed scheme is based on the adaptation of a highly efficient serial coupled-cluster code leading to a communication-minimized implementation by parallelizing the time-determining steps. The parallel algorithm is tailored for affordable cluster architectures connected by standard communication networks such as …
On enhancing the object migration automaton using the Pursuit paradigm
2017
Abstract One of the most difficult problems that is all-pervasive in computing is that of partitioning. It has applications in the partitioning of databases into relations, the realization of the relations themselves into sub-relations based on the partitioning of the attributes, the assignment of processes to processors, graph partitioning, and the task assignment problem, etc. The problem is known to be NP-hard. The benchmark solution for this for the Equi-Partitioning Problem (EPP) has involved the classic field of Learning Automata (LA), and the corresponding algorithm, the Object Migrating Automata (OMA) has been used in all of these application domains. While the OMA is a fixed struct…
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
2019
Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …
Combining finite learning automata with GSAT for the satisfiability problem
2010
A large number of problems that occur in knowledge-representation, learning, very large scale integration technology (VLSI-design), and other areas of artificial intelligence, are essentially satisfiability problems. The satisfiability problem refers to the task of finding a satisfying assignment that makes a Boolean expression evaluate to True. The growing need for more efficient and scalable algorithms has led to the development of a large number of SAT solvers. This paper reports the first approach that combines finite learning automata with the greedy satisfiability algorithm (GSAT). In brief, we introduce a new algorithm that integrates finite learning automata and traditional GSAT use…
Congenital hypothyroidism: A 2020-2021 consensus guidelines update-An ENDO-European Reference Network initiative endorsed by the European Society for…
2021
Background: An ENDO-European Reference Network (ERN) initiative was launched that was endorsed by the European Society for Pediatric Endocrinology and the European Society for Endocrinology with 22 participants from the ENDO-ERN and the two societies. The aim was to update the practice guidelines for the diagnosis and management of congenital hypothyroidism (CH). A systematic literature search was conducted to identify key articles on neonatal screening, diagnosis, and management of primary and central CH. The evidence-based guidelines were graded with the Grading of Recommendations, Assessment, Development and Evaluation system, describing both the strength of recommendations and the quali…
Komercbanku un uzņēmējdarbības savstarpējas ietekmes analīze.
2017
Bakalaurā darbā tiek pētīta uzņēmējdarbības un komercbanku mijiedarbība. Darbā tiek praktiski pielietota benčmārkinga teorija, salīdzinātie iegūti rezultāti, izveidojot trīsfaktoru lineārā un nelineārā regresiju, kā arī aprēķināti sezonālie indeksi ap pakāpes trendu. Ar benčmārkinga metodes praktisko pielietojumu tiek salīdzinātas lielākās komercbankas pēc korporatīvo klientu skaita. Iegūtie rezultāti, no klientu skata punkta, palīdzēja noteikt labāko komercbanku juridiskām personām, kā arī prognozēt izsniegto kopēju komerckredītu apjoma izmaiņas Latvijā tuvākā divu gada laikā.
Nowcasting Global Economic Growth: A Factor-Augmented Mixed-Frequency Approach
2014
Facing several economic and financial uncertainties, assessing accurately global economic conditions is a great challenge for economists. The International Monetary Fund proposes within its periodic World Economic Outlook report a measure of the global GDP annual growth, that is often considered as the benchmark nowcast by macroeconomists. In this paper, we put forward an alternative approach to provide monthly nowcasts of the annual global growth rate. Our approach builds on a Factor-Augmented MIxed DAta Sampling (FA-MIDAS) model that enables (i) to account for a large monthly database including various countries and sectors of the global economy and (ii) to nowcast a low-frequency macroec…