Stochastic Optimization

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1221–1230 of 1387 papers

Title	Date	Tasks	Status
Coupling Adaptive Batch Sizes with Learning Rates	Dec 15, 2016	image-classificationImage Classification	CodeCode Available
An empirical analysis of the optimization of deep network loss surfaces	Dec 13, 2016	Stochastic Optimization	—Unverified
One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities	Dec 1, 2016	General ClassificationLanguage Modeling	—Unverified
Without-Replacement Sampling for Stochastic Gradient Methods	Dec 1, 2016	Distributed OptimizationLearning Theory	—Unverified
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling	Nov 23, 2016	Language ModelingLanguage Modelling	—Unverified
Optimal Learning for Stochastic Optimization with Nonlinear Parametric Belief Models	Nov 22, 2016	Stochastic Optimization	—Unverified
Optimizing connection weights in neural networks using the whale optimization algorithm	Nov 21, 2016	Stochastic Optimization	—Unverified
Scalable Approximations for Generalized Linear Problems	Nov 21, 2016	Binary ClassificationGeneral Classification	—Unverified
Scalable Adaptive Stochastic Optimization Using Random Projections	Nov 21, 2016	Dimensionality ReductionStochastic Optimization	—Unverified
A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression	Nov 18, 2016	regressionStochastic Optimization	—Unverified

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All datasets CIFAR-100 WRN-28-10 - 200 Epochs CIFAR-10 WRN-28-10 - 200 Epochs CIFAR-10 ResNet-18 - 200 Epochs ImageNet ResNet-50 - 90 Epochs Penn Treebank (Character Level) 3x1000 LSTM - 500 Epochs CIFAR-10 CIFAR-100 ImageNet ResNet-50 - 50 Epochs ImageNet ResNet-50 - 60 Epochs AG News CoLA MNIST

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	AvaGrad	Accuracy	81.24	—	Unverified
2	AdaShift	Accuracy	81.12	—	Unverified
3	Adam (eps-adjusted)	Accuracy	81.04	—	Unverified
4	SGD	Accuracy	80.95	—	Unverified
5	AdamW	Accuracy	79.87	—	Unverified
6	AdaBound	Accuracy	77.24	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Adam (eps-adjusted)	Accuracy	96.36	—	Unverified
2	AvaGrad	Accuracy	96.2	—	Unverified
3	SGD	Accuracy	96.14	—	Unverified
4	AdaShift	Accuracy	95.92	—	Unverified
5	AdamW	Accuracy	95.89	—	Unverified
6	AdaBound	Accuracy	94.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SGD - cosine LR schedule	Accuracy	95.55	—	Unverified
2	Lookahead	Accuracy	95.27	—	Unverified
3	SGD	Accuracy	95.23	—	Unverified
4	ADAM	Accuracy	94.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AvaGrad	Top 1 Accuracy	76.51	—	Unverified
2	SGD	Top 1 Accuracy	75.99	—	Unverified
3	AdamW	Top 1 Accuracy	72.9	—	Unverified
4	AdaBound	Top 1 Accuracy	72.01	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AdaBound	Bit per Character (BPC)	2.86	—	Unverified
2	AdaShift	Bit per Character (BPC)	1.27	—	Unverified
3	AdamW	Bit per Character (BPC)	1.23	—	Unverified
4	AvaGrad	Bit per Character (BPC)	1.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Resnet18	Accuracy (max)	86.85	—	Unverified
2	Resnet34	Accuracy (max)	86.14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Resnet18	Accuracy (max)	58.48	—	Unverified
2	Resnet34	Accuracy (max)	54.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SGD	Top 5 Accuracy	92.15	—	Unverified
2	Lookahead	Top 1 Accuracy	75.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Lookahead	Top 1 Accuracy	75.49	—	Unverified
2	SGD	Top 1 Accuracy	75.15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Bert	Accuracy (max)	93.99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Bert	Accuracy (max)	86.34	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MLP	NLL	0.05	—	Unverified