On a Stochastic Approximation Method

By K. Chung. 1954

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1. Frank E. Curtis
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3. Yoshua Bengio
4. Dacheng Tao
5. Yann LeCun
6. Kaiming He
7. Quoc V. Le
8. Sebastian U. Stich

Citations in the corpus

• Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling (2020, unknown): “[4] Chung, K.”
• Item Response Theory—A Statistical Framework for Educational and Psychological Measurement (2021, unknown): “Cai (2010a,b) suggested to set the step size to delay at the rate 1 /t , which is known to be asymptotically optimal for the Robbins-Monro algorithm (Chung, 1954; Lai and Robbins, 1979).”
• On the convergence of single-call stochastic extra-gradient methods (2019, unknown): “[11] Chung, Kuo-Liang.”
• Optimization Methods for Large-Scale Machine Learning (2016, background): “tching can appear to be somewhat ambiguous, meaning that one must leverage 5In fact, the bound (4.21) slightly overstates the asymptotic in uence of the initial optimality gap. Applying Chung’s lemma [36] to the contraction equation (4.23) shows that the rst term in the denition of eectively determ”