Suchergebnisse - Exponentiated Gradient algorithm

Estimating the spectrum in computed tomography via Kullback–Leibler divergence constrained optimization von Ha, Wooseok, Sidky, Emil Y., Barber, Rina Foygel, Schmidt, Taly Gilat, Pan, Xiaochuan

“… The formulated constrained optimization problem is convex and can be solved efficiently by use of the exponentiated‐gradient (EG) algorithm …”
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EGRank: An exponentiated gradient algorithm for sparse learning-to-rank von Du, Lei, Pan, Yan, Ding, Jintang, Lai, Hanjiang, Huang, Changqin

“… An exponential gradient algorithm is proposed to learn sparse models for learning-to-rank, which can be formulated as a convex optimization problem with the ℓ1 constraint …”
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Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection von Cichocki, Andrzej, Cruces, Sergio, Sarmiento, Auxiliadora, Tanaka, Toshihisa

“… Stochastic gradient descent (SGD) and exponentiated gradient (EG) update methods are widely used in signal processing and machine learning …”
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A Class of Diffusion Zero Attracting Stochastic Gradient Algorithms With Exponentiated Error Cost Functions von Luo, Zhengyan, Zhao, Haiquan, Zeng, Xiangping

“… In this paper, a class of diffusion zero-attracting stochastic gradient algorithms with exponentiated error cost functions is put forward due to its good performance for sparse system identification …”
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Convergence of exponentiated gradient algorithms von Hill, S.I., Williamson, R.C.

“… This paper studies three related algorithms: the (traditional) gradient descent (GD) algorithm, the exponentiated gradient algorithm with positive and negative weights …”
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A Study of the Exponentiated Gradient +/- Algorithm for Stochastic Optimization of Neural Networks von Parks, David F

“… Exponentiated Gradient +/- (abbr. EG+-) is a gradient update algorithm drawn from work by Manfred Warmuth …”
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A class of stochastic gradient algorithms with exponentiated error cost functions von Boukis, C., Mandic, D.P., Constantinides, A.G.

“… A novel class of stochastic gradient descent algorithms is introduced based on the minimisation of convex cost functions with exponential dependence on the adaptation error, instead …”
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An Improved Exponentiated stochastic gradient algorithm von Rusu, C, Cowan, C F N

“… Recently, few stochastic gradient algorithms have been proposed and they are based on cost functions that have exponential dependence on the chosen error …”
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Kernelization of matrix updates, when and how? von Warmuth, Manfred K., Kotłowski, Wojciech, Zhou, Shuisheng

“… We define what it means for a learning algorithm to be kernelizable in the case when the instances are vectors, asymmetric matrices and symmetric matrices, respectively …”
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On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization von Garber, Dan, Kaplan, Atara

“… In particular, the desirable choice is the Matrix Exponentiated Gradient (MEG) method which is based on the Bregman distance induced by the (negative …”
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Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection von Cichocki, Andrzej, Cruces, Sergio, Sarmiento, Auxiliadora, Tanaka, Toshihisa

“… This paper introduces a novel family of generalized exponentiated gradient (EG) updates derived from an Alpha-Beta divergence regularization function …”
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Online variance minimization von Warmuth, Manfred K., Kuzmin, Dima

“… . For the first parameter space we apply the Exponentiated Gradient algorithm …”
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Energy-Efficient LSTM Networks for Online Learning von Ergen, Tolga, Mirza, Ali H., Kozat, Suleyman Serdar

“… For this structure, we also introduce highly effective online training algorithms. We first provide a generic LSTM-based regression structure for variable-length input sequences …”
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Optimistic optimisation of composite objective with exponentiated update von Shao, Weijia, Sivrikaya, Fikret, Albayrak, Sahin

“… The algorithms can be interpreted as the combination of the exponentiated gradient and p -norm algorithm …”
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Stochastic gradient algorithm based on an improved higher order exponentiated error cost function von Bin Mansoor, Umair, Asad, Syed Muhammad, Zerguine, Azzedine

“… We propose stochastic gradient algorithm based on exponentiated cost functions that employ higher order moments of the chosen error …”
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An exponentiated gradient adaptive algorithm for blind identification of sparse SIMO systems von Benesty, J., Yiteng Huang, Jingdong Chen

“… Sparse impulse responses are encountered in many acoustic and wireless channels. Recently, a class of exponentiated gradient (EG …”
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The LMS, PNLMS, and exponentiated gradient algorithms von Benesty, Jacob, Yiteng Huang

“… ). Recently, a class of exponentiated gradient (EG) algorithms has been proposed. One of the algorithms belonging to this class, the so-called EG …”
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A Comparison of New and Old Algorithms for a Mixture Estimation Problem von Helmbold, David P., Schapire, Robert E., Singer, Yoram, Warmuth, Manfred K.

“… We adapt a framework developed for supervised learning and give simple derivations for many of the standard iterative algorithms like gradient projection and EM …”
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Exponentiated Gradient Exploration for Active Learning von Bouneffouf, Djallel

“… more informative. In this setting, we propose a sequential algorithm named exponentiated gradient (EG)-active that can improve any active learning algorithm by an optimal random exploration …”
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An analysis of the exponentiated gradient descent algorithm von Hill, S.I., Williamson, R.C.

“… : the gradient descent (GD) algorithm, the exponentiated gradient algorithm with positive and negative weights …”
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