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projects:asgd:start [2015/02/11 17:09] hjprojects:asgd:start [2015/07/12 14:04] (current) hj
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 ====== Annealing SGD ====== ====== Annealing SGD ======
  
-===== Annealing Stochastic Gradient Descent (ASGD) =====+===== Annealed Stochastic Gradient Descent (AGD) =====
  
-{{ :projects:asgd:screen_shot_2015-02-11_at_12.08.29_pm.png?0x350 |}}+{{ :projects:asgd:screen_shot_2015-02-11_at_12.08.29_pm.png?0x500 |}} 
 +\\ 
 +\\ 
 +Here, we propose a novel annealed gradient descent (AGD) method for 
 +deep learning. AGD optimizes a sequence of gradually improved smoother mosaic 
 +functions that approximate the original non-convex objective function according 
 +to an annealing schedule during optimization process. We present a theoretical 
 +analysis on its convergence properties and learning speed. The proposed AGD 
 +algorithm is applied to learning deep neural networks (DNN) for image recognition 
 +in MNIST and speech recognition in Switchboard. 
 +\\
  
 +**Reference:** \\
 +
 +[1] //Hengyue Pan, Hui Jiang//, "Annealed Gradient Descent for Deep Learning", //Proc. of 31th Conference on Uncertainty in Artificial Intelligence (UAI 2015)//, July 2015. ( [[http://auai.org/uai2015/proceedings/papers/73.pdf|here]])
projects/asgd/start.1423674577.txt.gz · Last modified: 2015/02/11 17:09 by hj