• ViennaRNA

  • Referenced in 23 articles [sw10504]
  • which yields a single optimal structure, the partition function algorithm of (McCaskill 1990) which calculates ... probabilities in the thermodynamic ensemble, and the suboptimal folding algorithm of (Wuchty et.al 1999) which ... within a given energy range of the optimal energy. For secondary structure comparison, the package...
  • HyperLogLog

  • Referenced in 22 articles [sw02063]
  • abstract describes and analyses a near-optimal probabilistic algorithm, HyperLogLog, dedicated to estimating the number ... elements (the cardinality) of very large data ensembles. Using an auxiliary memory of m units ... original memory. For instance, the new algorithm makes it possible to estimate cardinalities well beyond ... memory of only 1.5 kilobytes. The algorithm parallelizes optimally and adapts to the sliding window...
  • PhaseMax

  • Referenced in 28 articles [sw24954]
  • formulate phase retrieval as a convex optimization problem, which we call PhaseMax. Unlike other convex ... that phase retrieval can be performed using algorithms initially designed for sparse signal recovery ... broad range of random measurement ensembles, and we analyze the impact of measurement noise...
  • Signal-3L

  • Referenced in 16 articles [sw26857]
  • ensemble classifier formed by fusing many individual OET-KNN (optimized evidence-theoretic K nearest neighbor ... secretory protein by a subsite-coupled discrimination algorithm; (3) determining the final cleavage site...
  • CIXL2

  • Referenced in 19 articles [sw03302]
  • propose a crossover operator for evolutionary algorithms with real values that is based ... offspring. Our aim is the optimization of the balance between exploration and exploitation ... used a set of functions to be optimized with regard to different criteria, such ... weight of each network in a ensemble of neural networks. The results obtained are above...
  • PSPSO

  • Referenced in 1 article [sw39417]
  • optimization. This paper reports a high-level python package for selecting machine learning algorithms ... ensembles of machine learning algorithms parameters by using the particle swarm optimization (PSO) algorithm named...
  • h2oEnsemble

  • Referenced in 1 article [sw33570]
  • stacking.” The Super Learner algorithm learns the optimal combination of the base learner fits ... shown that the super learner ensemble represents an asymptotically optimal system for learning...
  • RECFMM

  • Referenced in 6 articles [sw21760]
  • CILK in particular, which provides graph-theoretic optimal scheduling in adaptation to the dynamics ... parallel execution -- are employed. RECFMM supports multiple algorithm variants that mark the major advances with ... asymmetrical version where the source particle ensemble is not necessarily the same as the target...
  • Osprey

  • Referenced in 3 articles [sw21400]
  • realistic in silico modeling of proteins. These algorithms are based on three characteristics that make ... ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal ... search, guaranteeing that the computational predictions are optimal with respect to the input model. Here ... redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental...
  • RaSEn

  • Referenced in 3 articles [sw33917]
  • free ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm ... some random subspaces are generated and the optimal one is chosen to train the model...
  • GOMC

  • Referenced in 2 articles [sw27534]
  • physical properties of complex fluids. GPU Optimized Monte Carlo (GOMC) is open-source software ... Metropolis Monte Carlo algorithm. It supports simulations in a variety of ensembles, which include canonical...
  • PSOFuzzySVM-TMH

  • Referenced in 3 articles [sw27664]
  • using an optimization selection technique, particle swarm optimization, from both feature spaces. Finally, the selected ... form ensemble feature space. Fuzzy-support vector Machine is utilized as a classification algorithm...
  • greed

  • Referenced in 2 articles [sw41875]
  • with the Integrated Classification Likelihood. An ensemble of algorithms that enable the clustering of networks ... clustering is performed in combination by optimizing the Integrated Classification Likelihood (which is equivalent...
  • Moldy

  • Referenced in 5 articles [sw01311]
  • parallel code. The code has been optimized for high performance in both serial and parallel ... Beeman algorithm. Simulations may be performed in the usual NVE ensemble or in isobaric and/or...
  • IPFViewer

  • Referenced in 0 articles [sw35266]
  • other ensemble data. To find an optimal way to design algorithms and visualization methods...
  • rocTree

  • Referenced in 2 articles [sw40356]
  • Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified framework ... performance of survival trees and establish the optimality of the target hazard/survival function. The optimality...
  • LCE

  • Referenced in 5 articles [sw25277]
  • another, this is often sub-optimal. Cluster ensemble research solves this problem by automatically combining ... clustering result. However, many existing ensemble techniques use an association matrix to summarize sample-cluster ... ensemble methodology for microarray data clustering. RESULTS: The link-based cluster ensemble (LCE) method, presented ... usually outperforms the existing cluster ensemble algorithms in individual tests and, overall, is clearly class...
  • ASPIC

  • Referenced in 3 articles [sw17147]
  • splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number ... splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion ... resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload...
  • GBMCI

  • Referenced in 2 articles [sw11476]
  • gradient boosting algorithm for survival analysis via direct optimization of concordance index. Survival analysis focuses ... hazard functions. Our nonparametric model utilizes an ensemble of regression trees to determine...
  • AutoGL

  • Referenced in 1 article [sw38082]
  • automatically design the optimal machine learning algorithm for a given graph task. However, all current ... engineering, model training, hyper-parameter optimization, and auto ensemble. For each module, we provide numerous...