methodology-15
Stochastic Optimization
3260 papers • 126 benchmarks • 313 datasets
Stochastic Optimization is the task of optimizing certain objective functional by generating and using stochastic random variables. Usually the Stochastic Optimization is an iterative process of generating random variables that progressively finds out the minima or the maxima of the objective functional. Stochastic Optimization is usually applied in the non-convex functional spaces where the usual deterministic optimization such as linear or quadratic programming or their variants cannot be used. Source: ASOC: An Adaptive Parameter-free Stochastic Optimization Techinique for Continuous Variables
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Benchmarks
These leaderboards are used to track progress in stochastic-optimization-31
Trend
Dataset
Best Model
Actions
CIFAR-10 WRN-28-10 - 200 Epochs
CIFAR-10 WRN-28-10 - 200 Epochs
CIFAR-100 WRN-28-10 - 200 Epochs
CIFAR-100 WRN-28-10 - 200 Epochs
Libraries
iUse these libraries to find stochastic-optimization-31 models and implementations
2 papers 31,398
