Mathematical software

Adam
Referenced in 737 articles [sw22205]
algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates ... large in terms of data and/or parameters. The method is also appropriate for non-stationary ... very noisy and/or sparse gradients. The hyper-parameters have intuitive interpretations and typically require little ... best known results under the online convex optimization framework. Empirical results demonstrate that Adam works...

Hyperopt
Referenced in 42 articles [sw19219]
hyperopt: Distributed Asynchronous Hyper-parameter Optimization. Hyperopt is a Python library for serial and parallel...

PyKEEN
Referenced in 3 articles [sw34084]
through the integration of Optuna extensive hyper-parameter optimization (HPO) functionalities are provided...

PocketFlow
Referenced in 1 article [sw36239]
hyper-parameter optimization module to automatically search for the optimal combination of hyper-parameters. Furthermore...

DriveML
Referenced in 1 article [sw32864]
automated methods for model selection and hyper-parameter optimization of various algorithms such as random...

AutoGL
Referenced in 1 article [sw38082]
horizon to automatically design the optimal machine learning algorithm for a given graph task. However ... modules: auto feature engineering, model training, hyper-parameter optimization, and auto ensemble. For each module...

r_ml_stata
Referenced in 1 article [sw38736]
neighbor, support vector machine. It provides hyper-parameters’ optimal tuning via K-fold cross-validation...

c_ml_stata
Referenced in 1 article [sw38737]
neighbor, support vector machine. It provides hyper-parameters’ optimal tuning via K-fold cross-validation...

DeepDIVA
Referenced in 1 article [sw27025]
boilerplate code, keeping track of experiments, hyper-parameter optimization, and visualization of data and results...

Anomalib
Referenced in 1 article [sw41238]
tools, including experiment trackers, visualizers, and hyper-parameter optimizers, make it simple to design...

EMBER
Referenced in 1 article [sw38336]
detection. Results show that even without hyper-parameter optimization, the baseline EMBER model outperforms MalConv...

GSVM
Referenced in 3 articles [sw41785]
original optimization problem for SVM training, nor introduces new hyper-parameters. Experimentation carried...

krisp
Referenced in 1 article [sw14717]
also known as Gaussian process regression) and optimization of deterministic simulators. The toolbox consists ... kernels, hyper-parameter estimation, prediction, cross validation). 2. methods implementing Expected Improvement based optimization...

PyODDS
Referenced in 3 articles [sw38163]
database setup, algorithm selection, and hyper-parameter tuning. To fill this gap, we present PyODDS ... Outlier Detection with Database Support, which automatically optimizes an outlier detection pipeline...

LargeVis
Referenced in 6 articles [sw34905]
objective of which can be effectively optimized through asynchronous stochastic gradient descent with a linear ... both efficiency and effectiveness. The hyper-parameters of LargeVis are also much more stable over...

Hyperas
Referenced in 0 articles [sw38947]
very simple wrapper for convenient hyperparameter optimization. A very simple convenience wrapper around hyperopt ... simple template notation to define hyper-parameter ranges to tune...

AlphaClean
Referenced in 1 article [sw37879]
data cleaning is very different than hyper-parameter tuning for machine learning since the pipeline ... proposes a framework, called AlphaClean, that rethinks parameter tuning for data cleaning pipelines. AlphaClean provides ... allows AlphaClean to apply a number of optimizations including incremental evaluation of the quality measures...

Adam