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First-Order Methods for Nonconvex Quadratic Minimization., and . SIAM Rev., 62 (2): 395-436 (2020)Comparison of the Achievable Rates in OFDM and Single Carrier Modulation with I.I.D. Inputs., , and . CoRR, (2013)A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions., , , and . CoRR, (2023)Variance Reduction for Matrix Games., , , and . NeurIPS, page 11377-11388. (2019)Acceleration with a Ball Optimization Oracle., , , , , , and . NeurIPS, (2020)Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems., and . NeurIPS, page 10728-10738. (2018)A Rank-1 Sketch for Matrix Multiplicative Weights., , , and . COLT, volume 99 of Proceedings of Machine Learning Research, page 589-623. PMLR, (2019)Eventually-stationary policies for Markov decision models with non-constant discounting., and . VALUETOOLS, page 63. ICST/ACM, (2008)Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 17684-17744. PMLR, (2023)Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss., , , and . COLT, volume 134 of Proceedings of Machine Learning Research, page 866-882. PMLR, (2021)