Filters








395,077 Hits in 3.9 sec

Software Engineers vs. Machine Learning Algorithms: An Empirical Study Assessing Performance and Reuse Tasks [article]

Nathalia Nascimento, Carlos Lucena, Paulo Alencar, Donald Cowan
2018 arXiv   pre-print
In this paper, we present an empirical study that compares how software engineers and machine-learning algorithms perform and reuse tasks.  ...  Finally, we analyzed the results to understand which tasks are better performed by either humans or algorithms so that they can work together more effectively.  ...  In our empirical study, in which we have assessed performance and reuse tasks, we accepted three alternative hypotheses and rejected one: Accepted: 1) An ML-based approach improves the performance of  ... 
arXiv:1802.01096v2 fatcat:pe7gfh5zqbgdbne3vhhl5s375y

A Fusion Multiobjective Empire Split Algorithm

Liang Liang, Kalyana C. Veluvolu
2020 Journal of Control Science and Engineering  
In this paper, a fusion multiobjective empire split algorithm (FMOESA) is proposed.  ...  Given both good performance and nice properties, the proposed algorithm could be an alternative tool when dealing with multiobjective optimization problems.  ...  If the number of empire individuals is greater than N, the population is deleted to obtain the final N empires with better performance (lines 21-23 in Algorithm 1).  ... 
doi:10.1155/2020/8882086 fatcat:an5szjhnrratncigiyz7bmctjy

Statistical assessment of performance of algorithms for detrending RR series

Antonio Fasano, Valeria Villani
2015 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
In this paper, we extensively assess its performance on RR series through a statistical analysis.  ...  To the best of the authors' knowledge, it is the fastest algorithm for detrending RR series.  ...  In this paper we have extensively assessed its performance through a statistical analysis based on the empirical distribution function of the trend estimation error: the empirical distribution function  ... 
doi:10.1109/embc.2015.7319106 pmid:26737006 dblp:conf/embc/FasanoV15 fatcat:ghl6c5qipjgitkocigo6eyerqu

Recommendation of Process Discovery Algorithms Through Event Log Classification [chapter]

Damián Pérez-Alfonso, Osiel Fundora-Ramírez, Manuel S. Lazo-Cortés, Raciel Roche-Escobar
2015 Lecture Notes in Computer Science  
The traditional approaches use empirical assessment in order to recommend a suitable discovery algorithm. This is a time consuming and computationally expensive approach.  ...  Process discovery algorithms are process mining techniques focused on discovering process models starting from event logs.  ...  Classical approaches that select discovery algorithms based on empirical assessments are computationally expensive and time consuming.  ... 
doi:10.1007/978-3-319-19264-2_1 fatcat:hpzyboz6t5hpvhuvdljp553uue

How to assess and report the performance of a stochastic algorithm on a benchmark problem: mean or best result on a number of runs?

Mauro Birattari, Marco Dorigo
2006 Optimization Letters  
Some authors claim that reporting the best result obtained by a stochastic algorithm in a number of runs is more meaningful than reporting some central statistic.  ...  Notwithstanding the publication of a number of good methodological papers [3] [4] [5] [6] , many research works dealing with stochastic optimization algorithms still propose unsatisfactory empirical assessments  ...  Dorigo e-mail: mdorigo@ulb.ac.be the performance of the stochastic algorithm A.  ... 
doi:10.1007/s11590-006-0011-8 fatcat:m23hyywbovca7fyylnes6t3uqa

New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers

Alejandro Rodriguez-Ruiz, Jonas Teuwen, Suzan Vreemann, Ramona W Bouwman, Ruben E van Engen, Nico Karssemeijer, Ritse M Mann, Albert Gubern-Merida, Ioannis Sechopoulos
2017 Acta Radiologica  
performance with deep-learning algorithms.  ...  The 3D-CNN-EMPIRE had better performance than 3D-CNN-FBP (pAUC-EMPIRE ¼ 0.880 vs. pAUC-FBP ¼ 0.857; P < 0.001).  ...  Visual grading analysis study An absolute VGA observer study (26) was performed to assess several aspects of image quality in both reconstruction algorithms.  ... 
doi:10.1177/0284185117748487 pmid:29254355 pmcid:PMC6088454 fatcat:usxflzi6zvgwrazfqedlnupk7q

Teaching empirical analysis of algorithms

Ian Sanders
2002 Proceedings of the 33rd SIGCSE technical symposium on Computer science education - SIGCSE '02  
In this paper I argue that empirical analysis of algorithms is important but also difficult and requires a place in our curricula.  ...  I discuss how I planned to include coverage of this topic through lectures, discussions and practical work and the approach that I took in the Honours Analysis of Algorithms topic at the University of  ...  Assessing the approach The students' performance The students were formally assessed on this material by a mini-assignment (designing an experiment for the empirical verification of the theoretical analysis  ... 
doi:10.1145/563467.563468 fatcat:2i3bdz3kmneuxpvlvyyqsil5hu

Teaching empirical analysis of algorithms

Ian Sanders
2002 Proceedings of the 33rd SIGCSE technical symposium on Computer science education - SIGCSE '02  
In this paper I argue that empirical analysis of algorithms is important but also difficult and requires a place in our curricula.  ...  I discuss how I planned to include coverage of this topic through lectures, discussions and practical work and the approach that I took in the Honours Analysis of Algorithms topic at the University of  ...  Assessing the approach The students' performance The students were formally assessed on this material by a mini-assignment (designing an experiment for the empirical verification of the theoretical analysis  ... 
doi:10.1145/563340.563468 dblp:conf/sigcse/Sanders02 fatcat:33azovrd6ra53n6whc43x7ibqm

Teaching empirical analysis of algorithms

Ian Sanders
2002 ACM SIGCSE Bulletin  
In this paper I argue that empirical analysis of algorithms is important but also difficult and requires a place in our curricula.  ...  I discuss how I planned to include coverage of this topic through lectures, discussions and practical work and the approach that I took in the Honours Analysis of Algorithms topic at the University of  ...  Assessing the approach The students' performance The students were formally assessed on this material by a mini-assignment (designing an experiment for the empirical verification of the theoretical analysis  ... 
doi:10.1145/563517.563468 fatcat:l5w5mt3o6rbuzbo76yfihsqwwa

A Systematic Review of the Application and Empirical Investigation of Search-Based Test Case Generation

Shaukat Ali, Lionel C. Briand, Hadi Hemmati, Rajwinder Kaur Panesar-Walawege
2010 IEEE Transactions on Software Engineering  
The intent is to aid future researchers doing empirical studies in SBST by providing an unbiased view of the body of empirical evidence and by guiding them in performing well-designed and executed empirical  ...  We also provide a framework that drives the data collection process of this systematic review and can be the starting point of guidelines on how SBST techniques can be empirically assessed.  ...  The cost and effectiveness of an SBST technique are used together for assessing its performance.  ... 
doi:10.1109/tse.2009.52 fatcat:ppyljmmwrbcfxnx52jifnenjfa

Benchmarking for Metaheuristic Black-Box Optimization: Perspectives and Open Challenges [article]

Ramses Sala, Ralf Müller
2020 arXiv   pre-print
For many of the commonly used synthetic benchmark problems or artificial fitness landscapes, there are however, no methods available, to relate the resulting algorithm performance assessments to technologically  ...  Besides a huge variety of different evolutionary and metaheuristic optimization algorithms, also a large number of test problems and benchmark suites have been developed and used for comparative assessments  ...  In the absence of theoretical methods to determine heuristic optimization algorithm performance on specific non-trivial problems, empirical algorithm performance analysis seems the last resort [21] .  ... 
arXiv:2007.00541v1 fatcat:ed7b4nhdmbc5jclu7qgx2zbgwm

Benchmarking for Metaheuristic Black-Box Optimization: Perspectives and Open Challenges

Ramses Sala, Ralf Muller
2020 2020 IEEE Congress on Evolutionary Computation (CEC)  
For many of the commonly used synthetic benchmark problems or artificial fitness landscapes, there are however, no methods available, to relate the resulting algorithm performance assessments to technologically  ...  Besides a huge variety of different evolutionary and metaheuristic optimization algorithms, also a large number of test problems and benchmark suites have been developed and used for comparative assessments  ...  In the absence of theoretical methods to determine heuristic optimization algorithm performance on specific non-trivial problems, empirical algorithm performance analysis seems the last resort [21] .  ... 
doi:10.1109/cec48606.2020.9185593 dblp:conf/cec/SalaM20 fatcat:l4cliyfwsve7rdsmevj44f4oza

A comparison of AdaBoost algorithms for time series forecast combination

Devon K. Barrow, Sven F. Crone
2016 International Journal of Forecasting  
Also, none of the algorithms have been assessed on a representative set of empirical data, using only few synthetic time series.  ...  Despite their theoretical promise their empirical accuracy in forecasting has not yet been assessed, either against each other or against any established approaches of forecast combination, model selection  ...  Empirical results on Forecast Accuracy Relative performance of forecast combination algorithms Following a systematic assessment of the impact of different meta-parameters, we assess Results show that  ... 
doi:10.1016/j.ijforecast.2016.01.006 fatcat:jlhndcfk4fc3xpfki3lrqyha7m

Comparing Imperialist Competitive Algorithm With Backpropagation Algorithms For Training Feedforward Neural Network

Maryam Zanganeh, Seyed Javad Mirabedini
2015 Journal of Mathematics and Computer Science  
Also, Accuracy and Mean Squared Error (MSE) are the main measures selected to assess both models. Also the MSE was used as a criterion to specify optimum number of neurons in the hidden layer.  ...  Mostly Back Propagation (BP) algorithm is a gradient descent algorithm (a first-order optimization algorithm) on the error space, which most likely gets trapped into a local minimum and has very slow convergence  ...  Model performance assessment criteria The performance assessment criteria used in this study include Accuracy and MSE.  ... 
doi:10.22436/jmcs.014.03.02 fatcat:a2b4decmhzbcjmpaf32qja3yoe

Expert-augmented machine learning

Efstathios D. Gennatas, Jerome H. Friedman, Lyle H. Ungar, Romain Pirracchio, Eric Eaton, Lara G. Reichmann, Yannet Interian, José Marcio Luna, Charles B. Simone, Andrew Auerbach, Elier Delgado, Mark J. van der Laan (+2 others)
2020 Proceedings of the National Academy of Sciences of the United States of America  
Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert.  ...  Filtering the rules based on the extent of disagreement between clinician-assessed risk and empirical risk, we improved performance on out-of-sample data and were able to train with less data.  ...  Filtering the rules based on the extent of disagreement between clinician-assessed risk and empirical risk, we improved performance on out-of-sample data and were able to train with less data.  ... 
doi:10.1073/pnas.1906831117 pmid:32071251 fatcat:yovbwu3vznfy5ppdea4puqndgy
« Previous Showing results 1 — 15 out of 395,077 results