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In this paper, we introduce an unbiased gradient simulation algorithms for solving convex optimization problem with stochastic function compositions.
Regression models and life tables (with discussion)
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The viterbi algorithm
G. D. Forney · 1973
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David R Cox · 1975
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Maximum likelihood from incomplete data via the em algorithm
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Conditional random fields: Probabilistic models for segmenting and labeling sequence data
John Lafferty, Andrew McCallum, and Fernando CN Pereira · 2001
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Shallow parsing with conditional random fields
Fei Sha and Fernando Pereira · 2003
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Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons
Andrew McCallum and Wei Li · 2003
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Ben Taskar, Carlos Guestrin, and Daphne Koller · 2004
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Accelerated training of conditional random fields with stochastic gradient methods
SVN Vishwanathan, Nicol N Schraudolph, Mark W Schmidt, and Kevin P Murphy · 2006
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Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
Charles Sutton, Andrew McCallum, and Khashayar Rohanimanesh · 2007
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Structured learning and prediction in computer vision
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Lin Xiao and Tong Zhang · 2014
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Linear convergence of variance-reduced stochastic gradient without strong convexity
Unbiased monte carlo for optimization and functions of expectations via multi-level randomization
Jose H Blanchet and Peter W Glynn · 2015
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Stopwasting my gradients: Practical svrg
Reza Harikandeh, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konečnỳ, and Scott Sallinen · 2015
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Competing with the empirical risk minimizer in a single pass
Roy Frostig, Rong Ge, Sham M Kakade, and Aaron Sidford · 2015
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Non-uniform stochastic average gradient method for training conditional random fields
Mark Schmidt, Reza Babanezhad, Mohamed Ahmed, Aaron Defazio, Ann Clifton, and Anoop Sarkar · 2015
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Accelerating stochastic composition optimization
Mengdi Wang and Ji Liu · 2016
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Improved svrg for non-strongly-convex or sum-of-non-convex objectives
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Pinghua Gong and Jieping Ye · 2014
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Saga: A fast incremental gradient method with support for non-strongly convex composite objectives
Aaron Defazio, Francis Bach, and Simon Lacoste-Julien · 2014
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Unbiased estimation with square root convergence for sde models
Chang-Han Rhee and Peter W. Glynn · 2015
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Minimizing finite sums with the stochastic average gradient
Mark Schmidt, Nicolas Le Roux, and Francis Bach
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Zeyuan Allen-Zhu and Yang Yuan · 2016
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Stochastic compositional gradient descent: Algorithms for minimizing compositions of expected-value functions
Mengdi Wang, Ethan X Fang, and Han Liu · 2017
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Finite-sum Composition Optimization via Variance Reduced Gradient Descent
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