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Stochastic gradient descent
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11	Data Stream Classification using Random Feature Functions and Novel Method Combinations Jesse Read Albert Bifet Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2015-08-21 10:06:56 Machine learning Artificial intelligence Learning Statistical classification Massive Online Analysis K-nearest neighbors algorithm Ensemble learning Classifier chains Multi-label classification Concept drift Stochastic gradient descent Naive Bayes classifier
12	PDF Document Add to Reading List Source URL: www.work.caltech.edu Language: English - Date: 2015-01-01 11:20:46 Mathematics Statistics Regression analysis Mathematical analysis Estimation theory Computational statistics Linear regression Stochastic gradient descent Cross entropy Gradient descent Derivative Euclidean vector
13	A Variational Analysis of Stochastic Gradient Algorithms Stephan Mandt Columbia University, Data Science Institute, New York, USA SM 3976@ COLUMBIA . EDU Add to Reading List Source URL: jmlr.org Language: English - Date: 2016-07-20 01:41:10 Statistics Mathematical analysis Statistical theory Estimation theory Bayesian statistics Stochastic optimization Probability theory Computational statistics Expectationmaximization algorithm Stochastic gradient descent OrnsteinUhlenbeck process Variational Bayesian methods
14	Simple, Efficient, and Neural Algorithms for Sparse Coding Sanjeev Arora∗ Princeton University, Computer Science Department Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:35 Mathematics Numerical analysis Algebra Linear algebra Convex optimization Operations research Computational statistics Mathematical optimization K-SVD Sparse approximation Deep learning Stochastic gradient descent
15	Journal of Machine Learning Research2159 Submitted 3/10; Revised 3/11; Published 7/11 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization∗ Add to Reading List Source URL: www.jmlr.org Language: English - Date: 2011-07-05 16:26:18 Mathematical optimization Numerical analysis Mathematical analysis Convex optimization Stochastic optimization Machine learning Gradient descent Stochastic gradient descent Subgradient method Proximal gradient methods for learning Perceptron BroydenFletcherGoldfarbShanno algorithm
16	Revisiting natural gradient for deep networks Yoshua Bengio Universit´e de Montr´eal Montr´eal QC H3C 3J7 Canada Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-02-18 01:51:44 Numerical analysis Mathematical analysis Mathematics Estimation theory Numerical linear algebra M-estimators Stochastic optimization Conjugate gradient method Nonlinear conjugate gradient method Gradient descent Gradient method Hessian matrix
17	Batch-Incremental vs. Instance-Incremental Learning in Dynamic and Evolving Data Jesse Read1 , Albert Bifet2 , Bernhard Pfahringer2 , Geoff Holmes2 1 Department of Signal Theory and Communications Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2012-10-25 03:54:39 Statistics Machine learning Learning Artificial intelligence Statistical classification Data mining Concept drift Massive Online Analysis K-nearest neighbors algorithm Support vector machine Stochastic gradient descent Batch processing
18	CS168: The Modern Algorithmic Toolbox Lecture #6: Stochastic Gradient Descent and Regularization Tim Roughgarden & Gregory Valiant∗ April 13, 2016 Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-06-04 09:49:44 Statistics Numerical analysis Mathematics Computational statistics Regression analysis Econometrics Convex optimization Estimation theory Stochastic gradient descent Gradient descent Linear regression Mathematical optimization
19	JMLR: Workshop and Conference Proceedings vol 40:1–46, 2015 Escaping From Saddle Points – Online Stochastic Gradient for Tensor Decomposition Rong Ge Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:36 Mathematical analysis Numerical analysis Mathematical optimization Multivariable calculus Convex analysis Stochastic optimization Convex optimization Stochastic gradient descent Hessian matrix Gradient descent Lagrange multiplier Higher-order singular value decomposition
20	Advances in the Minimization of Finite Sums Mark Schmidt Joint work with Nicolas Le Roux, Francis Bach, Reza Babanezhad and Mohamed Ahmed University of British Columbia Context: Minimizing Finite Sums Add to Reading List Source URL: www.proba.jussieu.fr Language: English Numerical analysis Numerical linear algebra Stochastic optimization Gradient descent Support vector machine Gradient method Operations research Mathematical optimization Stochastic gradient descent Stochastic approximation

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