
ProbLog
 Referenced in 99 articles
[sw06945]
 various approximate methods. ProbLog1 also supports parameter learning, in both the learning from entailment ... learning from interpretations setting. ProbLog1 also supports decisiontheoretic inference. ProbLog2 allows the user ... evidence). ProbLog2 also supports parameter learning in the learning from interpretations setting...

bnlearn
 Referenced in 74 articles
[sw08265]
 package bnlearn: Bayesian network structure learning, parameter learning and inference. Bayesian network structure learning, parameter ... Search) and hybrid (MMHC and RSMAX2) structure learning algorithms for both discrete and Gaussian networks ... included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional...

LIBSVM
 Referenced in 1185 articles
[sw04879]
 LIBSVM has gained wide popularity in machine learning and many other areas. In this article ... theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail: http://dl.acm.org...

BNT
 Referenced in 72 articles
[sw07384]
 distributions), exact and approximate inference, parameter and structure learning, and static and dynamic models...

glasso
 Referenced in 456 articles
[sw07432]
 graphical lasso [5] is an algorithm for learning the structure in an undirected Gaussian graphical ... models for different values of the tuning parameter. Convergence of glasso can be tricky...

LibDAI
 Referenced in 15 articles
[sw06422]
 probability distributions and maximum probability states. Parameter learning is also supported. A feature comparison with...

CTBNRLE
 Referenced in 6 articles
[sw12961]
 learning, CTBNRLE implements structure and parameter learning for both complete and partial data...

Xception
 Referenced in 23 articles
[sw39068]
 Xception: Deep Learning with Depthwise Separable Convolutions. We present an interpretation of Inception modules ... Xception architecture has the same number of parameters as Inception V3, the performance gains...

Evigan
 Referenced in 5 articles
[sw14331]
 model is a dynamic Bayes network whose parameters are adjusted to maximize the probability ... matches, and splice site predictions; learned parameters encode the relative quality of evidence sources. Since...

mlr
 Referenced in 31 articles
[sw12357]
 Machine Learning in R. Interface to a large number of classification and regression techniques, including ... machinereadable parameter descriptions. There is also an experimental extension for survival analysis, clustering ... general, examplespecific costsensitive learning. Generic resampling, including crossvalidation, bootstrapping and subsampling. Hyperparameter...

SLEP
 Referenced in 41 articles
[sw13487]
 SLEP: Sparse Learning with Efficient Projections. Main Features: 1) FirstOrder Method. At each iteration ... solutions corresponding to a series of regularization parameters by the “warmstart” technique...

CONTRAfold
 Referenced in 8 articles
[sw17117]
 fullyautomated statistical learning algorithms to derive model parameters. Despite this advantage, however, probabilistic methods ... statistical learning procedures provide an effective alternative to empirical measurement of thermodynamic parameters...

CONTRAlign
 Referenced in 4 articles
[sw08305]
 extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair...

SMAC
 Referenced in 80 articles
[sw27215]
 tool for optimizing algorithm parameters (or the parameters of some other process ... effective for the hyperparameter optimization of machine learning algorithms, scaling better to high dimensions ... tasks that are more scientifically valuable than parameter tuning...

OKVARBoost
 Referenced in 3 articles
[sw24063]
 operatorvalued kernels that simultaneously learns the model parameters, as well as the network structure ... developed to perform the tasks of parameter learning and network inference for the proposed model...

ParseNet
 Referenced in 6 articles
[sw36638]
 global feature, and a technique for learning normalization parameters, accuracy increases consistently even over...

PyMix
 Referenced in 2 articles
[sw07781]
 specific independence structure learning; Partially supervised parameter learning; Parameter estimation for pairwise constrained samples...

Pegasos
 Referenced in 103 articles
[sw08752]
 where λ is the regularization parameter of SVM. For a linear kernel, the total ... resulting algorithm is especially suited for learning from large datasets. Our approach also extends...

SYNTHIA Dataset
 Referenced in 7 articles
[sw35060]
 visual tasks. However, DCNNs require learning of many parameters from raw images, thus, having...

MIxBN
 Referenced in 1 article
[sw39155]
 algorithm that allows structural learning and parameters learning from mixed data without discretization since data ... regression and Gaussian distribution approximation for parameters learning. The library also offers two algorithms ... follows: (1) structural and parameters learning of a Bayesian network on discretized data, (2) structural ... parameters learning of a Bayesian network on mixed data using the MI mixed score function...