Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

SotA/Methodology/Stochastic Optimization

Stochastic Optimization

19 benchmarks1387 papers

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.

<span class="description-source">Source: ASOC: An Adaptive Parameter-free Stochastic Optimization Techinique for Continuous Variables </span>

Benchmarks

Stochastic Optimization on CIFAR-10 WRN-28-10 - 200 Epochs

Stochastic Optimization on CIFAR-100 WRN-28-10 - 200 Epochs

Stochastic Optimization on CIFAR-10 ResNet-18 - 200 Epochs

Stochastic Optimization on ImageNet ResNet-50 - 90 Epochs

Stochastic Optimization on Penn Treebank (Character Level) 3x1000 LSTM - 500 Epochs

Bit per Character (BPC)

Stochastic Optimization on CIFAR-10

Accuracy (max)Accuracy (mean)

Stochastic Optimization on CIFAR-100

Accuracy (max)Accuracy (mean)

Stochastic Optimization on ImageNet ResNet-50 - 60 Epochs

Top 5 Accuracy Top 1 Accuracy

Stochastic Optimization on AG News

Accuracy (max)Accuracy (mean)

Stochastic Optimization on CoLA

Accuracy (max)Accuracy (mean)

Stochastic Optimization on MNIST

Stochastic Optimization on ^(#$!@#$)(()))******

Stochastic Optimization on ImageNet ResNet-50 - 50 Epochs

Top 1 Accuracy Top 5 Accuracy