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 631–640 of 1387 papers

Title	Date	Tasks	Status	Hype
Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network	Jun 1, 2021	ImputationMissing Values	—Unverified	0
Combining resampling and reweighting for faithful stochastic optimization	May 31, 2021	Computational chemistryStochastic Optimization	—Unverified	0
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks	May 28, 2021	Deep LearningStochastic Optimization	CodeCode Available	0
Last iterate convergence of SGD for Least-Squares in the Interpolation regime.	May 21, 2021	Stochastic Optimization	—Unverified	0
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees	May 21, 2021	Stochastic Optimizationvalid	—Unverified	0
Gradient Clipping Helps in Non-Smooth Stochastic Optimization with Heavy-Tailed Noise	May 21, 2021	Stochastic Optimization	—Unverified	0
Dynamic Trajectory and Offloading Control of UAV-enabled MEC under User Mobility	May 19, 2021	Stochastic Optimization	—Unverified	0
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD	May 17, 2021	Stochastic Optimization	—Unverified	0
Efficient Stochastic Optimal Control through Approximate Bayesian Input Inference	May 17, 2021	Stochastic Optimization	CodeCode Available	1
How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function	May 14, 2021	BIG-bench Machine LearningStochastic Optimization	—Unverified	0

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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