Dataset Groups Activity Stream Stochastic Trust Region and Cubic Regularization Methods for Non-convex Optimization The dataset used in this paper is a finite-sum minimization problem, where each sample is a convex quadratic function. BibTex: @dataset{Liu_Liu_and_Xuanqing_Liu_and_Cho-Jui_Hsieh_and_Dacheng_Tao_2024, abstract = {The dataset used in this paper is a finite-sum minimization problem, where each sample is a convex quadratic function.}, author = {Liu Liu and Xuanqing Liu and Cho-Jui Hsieh and Dacheng Tao}, doi = {10.57702/ua41m8fl}, institution = {No Organization}, keyword = {'finite-sum minimization', 'machine learning', 'non-convex optimization'}, month = {dec}, publisher = {TIB}, title = {Stochastic Trust Region and Cubic Regularization Methods for Non-convex Optimization}, url = {https://service.tib.eu/ldmservice/dataset/stochastic-trust-region-and-cubic-regularization-methods-for-non-convex-optimization}, year = {2024} }
