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Quasi-Newton methods for machine learning: forget the past, just sample., , , and . Optim. Methods Softw., 37 (5): 1668-1704 (2022)Underestimate Sequences via Quadratic Averaging., , , , and . CoRR, (2017)Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information., , , , , and . CoRR, (2021)Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information., , , , , and . ICLR, OpenReview.net, (2022)Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences., , , , and . Comput. Optim. Appl., 79 (2): 369-404 (2021)Quasi-Newton Methods for Deep Learning: Forget the Past, Just Sample., , and . CoRR, (2019)Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy., , , , , , and . CoRR, (2018)Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1., , , , and . LOD (1), volume 12565 of Lecture Notes in Computer Science, page 41-54. Springer, (2020)DynNet: Physics-based neural architecture design for linear and nonlinear structural response modeling and prediction., , , and . CoRR, (2020)Don't Forget Your Teacher: A Corrective Reinforcement Learning Framework., , , and . CoRR, (2019)