Results 61 to 70 of about 1,424,164 (189)
Distributed Stochastic Gradient Descent With Compressed and Skipped Communication
IEEE Access, 2023 This paper introduces CompSkipDSGD, a new algorithm for distributed stochastic gradient descent that aims to improve communication efficiency by compressing and selectively skipping communication.
Tran Thi Phuong +2 more
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Graph Drawing by Stochastic Gradient Descent [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2019 Submitted to IEEE Transactions on Visualization and Computer Graphics on 26/06 ...
Jonathan X. Zheng +2 more
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Equating quantum imaginary time evolution, Riemannian gradient flows, and stochastic implementations
Physical Review ResearchWe identify quantum imaginary time evolution as a Riemannian gradient flow on the unitary group. We develop an upper bound for the error between the two evolutions that can be controlled through the step size of the Riemannian gradient descent that ...
Nathan A. McMahon +2 more
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Stochastic Adaptive Gradient Descent Without Descent
CoRRWe introduce a new adaptive step-size strategy for convex optimization with stochastic gradient that exploits the local geometry of the objective function only by means of a first-order stochastic oracle and without any hyper-parameter tuning. The method comes from a theoretically-grounded adaptation of the Adaptive Gradient Descent Without Descent ...
Castera, Camille +2 more
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On Scalable Inference with Stochastic Gradient Descent
CoRR, 2017 In many applications involving large dataset or online updating, stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates and has gained increasing popularity due to its numerical convenience and memory efficiency. While the asymptotic properties of SGD-based estimators have been established decades ago, statistical ...
Yixin Fang, Jinfeng Xu, Lei Yang
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Text Sentiment Analysis Based on Hybrid Chi-square Statistic and Logistic Regression [PDF]
Jisuanji gongcheng, 2017 In text sentiment analysis,feature extraction method based on Chi-square statistic (CHI) is easy to ignore single text word frequency which leads to text feature accuary is low,a feature extraction method based on hybrid chi-square statistics is proposed.
LI Ping,DAI Yueming,WANG Yan
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Fractional Stochastic Search Algorithms: Modelling Complex Systems via AI
Mathematics, 2023 The aim of this article is to establish a stochastic search algorithm for neural networks based on the fractional stochastic processes {BtH,t≥0} with the Hurst parameter H∈(0,1).
Bodo Herzog
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Stochastic Gradient Descent for Risk Optimization
, 2020 This paper presents an approach for the use of stochastic gradient descent methods for the solution of risk optimization problems. The first challenge is to avoid the high-cost evaluation of the failure probability and its gradient at each iteration of ...
Lopez, Rafael Holdorf +7 more
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On the Generalization of Stochastic Gradient Descent with Momentum
J. Mach. Learn. Res., 2018 While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that there exists a convex loss function for which the stability gap for multiple epochs of SGD with ...
Ramezani-Kebrya, Ali +4 more
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Attentional-Biased Stochastic Gradient Descent
Trans. Mach. Learn. Res., 2020 In this paper, we present a simple yet effective provable method (named ABSGD) for addressing the data imbalance or label noise problem in deep learning. Our method is a simple modification to momentum SGD where we assign an individual importance weight to each sample in the mini-batch.
Qi Qi 0006 +4 more
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