Application of linear regression algorithm and stochastic gradient descent in a machine‐learning environment for predicting biomass higher heating value
Sign Up to like & getrecommendations! Published in 2020 at "Biofuels"
DOI: 10.1002/bbb.2140
Abstract: The higher heating value (HHV) provides information about the quantity of energy contained in a fuel such as biomass. Correlations and models can be developed to predict biomass HHV quickly from other analysis data. In… read more here.
Keywords: stochastic gradient; heating value; regression algorithm; linear regression ... See more keywords
Hierarchical Stochastic Gradient Algorithm and its Performance Analysis for a Class of Bilinear-in-Parameter Systems
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DOI: 10.1007/s00034-016-0367-7
Abstract: This paper considers the parameter identification for a special class of nonlinear systems, i.e., bilinear-in-parameter systems. Based on the hierarchical identification principle, a hierarchical stochastic gradient (HSG) estimation algorithm is presented. The basic idea is… read more here.
Keywords: algorithm; class; parameter systems; bilinear parameter ... See more keywords
Recursive Least Squares and Multi-innovation Stochastic Gradient Parameter Estimation Methods for Signal Modeling
Sign Up to like & getrecommendations! Published in 2017 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-016-0378-4
Abstract: The sine signals are widely used in signal processing, communication technology, system performance analysis and system identification. Many periodic signals can be transformed into the sum of different harmonic sine signals by using the Fourier… read more here.
Keywords: parameter estimation; estimation; stochastic gradient; innovation ... See more keywords
Aitken-Based Stochastic Gradient Algorithm for ARX Models with Time Delay
Sign Up to like & getrecommendations! Published in 2019 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-018-0998-y
Abstract: This paper proposes an Aitken-based stochastic gradient algorithm for ARX models with time delay. By using the redundant rule, the ARX model can be transformed into an augmented model. Based on the Aitken method, the… read more here.
Keywords: aitken based; stochastic gradient; gradient algorithm; based stochastic ... See more keywords
A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Control, Automation and Systems"
DOI: 10.1007/s12555-016-0081-z
Abstract: For a multivariable system with moving average noise (i.e., a multivariable controlled autoregressive moving average system), this paper proposes a filtering based extended stochastic gradient (ESG) algorithm and a filtering based multi-innovation ESG algorithm for… read more here.
Keywords: filtering based; multi innovation; extended stochastic; based multi ... See more keywords
Maximum Likelihood Multi-innovation Stochastic Gradient Estimation for Multivariate Equation-error Systems
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Control, Automation and Systems"
DOI: 10.1007/s12555-017-0538-8
Abstract: This paper focuses on the parameter estimation problems of multivariate equation-error systems. A multi-innovation generalized extended stochastic gradient algorithm is presented as a comparison. Based on the maximum likelihood principle and the coupling identification concept,… read more here.
Keywords: multi innovation; stochastic gradient; maximum likelihood; multivariate equation ... See more keywords
An adaptive mini-batch stochastic gradient method for AUC maximization
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.08.041
Abstract: Abstract Due to the wide applications in imbalanced learning, directly optimizing AUC has gained increasing interest in recent years. Compared with traditional batch learning methods, which often suffer from poor scalability, it is more challenging… read more here.
Keywords: gradient method; method auc; batch; gradient ... See more keywords
Energy–entropy competition and the effectiveness of stochastic gradient descent in machine learning
Sign Up to like & getrecommendations! Published in 2018 at "Molecular Physics"
DOI: 10.1080/00268976.2018.1483535
Abstract: ABSTRACT Finding parameters that minimise a loss function is at the core of many machine learning methods. The Stochastic Gradient Descent (SGD) algorithm is widely used and delivers state-of-the-art results for many problems. Nonetheless, SGD… read more here.
Keywords: machine learning; gradient descent; energy; physics ... See more keywords
On the rates of convergence of parallelized averaged stochastic gradient algorithms
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DOI: 10.1080/02331888.2020.1764557
Abstract: ABSTRACT The growing interest for high-dimensional and functional data analysis led in the last decade to important research developing a consequent amount of techniques. Parallelized algorithms, which consist of distributing and treat the data into… read more here.
Keywords: averaged stochastic; rates convergence; stochastic gradient; parallelized averaged ... See more keywords
Deep learning for sea cucumber detection using stochastic gradient descent algorithm
Sign Up to like & getrecommendations! Published in 2020 at "European Journal of Remote Sensing"
DOI: 10.1080/22797254.2020.1715265
Abstract: ABSTRACT A large number of natural products secluded from sea atmosphere has been identified for the pharmacodynamic probable in varied illness handlings, such as, tumor or inflammatory states. Sea cucumber culturing and fishing is mainly… read more here.
Keywords: cucumber detection; sea; stochastic gradient; sea cucumber ... See more keywords
Fractional Stochastic Gradient Algorithm for Time-Delayed Models With Piece-Wise Linear Input Using Self-Organizing Maps Method
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3228788
Abstract: Although stochastic gradient algorithm can identify linear systems with high efficiency. It is inefficient for nonlinear systems for the difficulty in the step-size designing. To overcome this dilemma, this paper proposes a fractional stochastic gradient… read more here.
Keywords: stochastic gradient; gradient algorithm; fractional stochastic; piece wise ... See more keywords