预测 发表于 2025-3-26 22:28:53
http://reply.papertrans.cn/88/8779/877858/877858_31.pngDecongestant 发表于 2025-3-27 04:18:55
Multiple Timescales,In the preceding chapters, we have used a fixed stepsize schedule . for all components of the iterations in stochastic approximation. In the ‘o.d.e. approach’ to the analysis of stochastic approximation, these are viewed as discrete nonuniform time steps.眉毛 发表于 2025-3-27 08:06:10
http://reply.papertrans.cn/88/8779/877858/877858_33.pngFLAX 发表于 2025-3-27 11:33:38
http://reply.papertrans.cn/88/8779/877858/877858_34.pngSeminar 发表于 2025-3-27 15:29:21
Stochastic Gradient Schemes,By far the most frequently applied instance of stochastic approximation is the stochastic gradient descent (or ascent) algorithm and its many variants. As the name suggests, these are noisy cousins of the eponymous algorithms from optimization that seek to minimize or maximize a given performance measure.Conscientious 发表于 2025-3-27 19:10:05
,Liapunov and Related Systems,We consider here algorithms which cannot be cast as stochastic gradient schemes, but have associated with their limiting (.-dimensional) o.d.e.Jubilation 发表于 2025-3-27 22:53:27
Vivek S. BorkarPresents a comprehensive view of the ODE-based approach for the analysis of stochastic approximation algorithms.Discusses important themes on stability tests, concentration bounds, and avoidance of trPRE 发表于 2025-3-28 03:44:20
http://reply.papertrans.cn/88/8779/877858/877858_38.png溃烂 发表于 2025-3-28 07:15:20
http://reply.papertrans.cn/88/8779/877858/877858_39.png受辱 发表于 2025-3-28 12:40:54
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