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Gradient Descent Converges to Minimizers: The Case of Non-Isolated Critical Points., and . CoRR, (2016)First-order Methods Almost Always Avoid Saddle Points., , , , , and . CoRR, (2017)Near-Optimality in Covering Games by Exposing Global Information., , , and . ACM Trans. Economics and Comput., 2 (4): 13:1-13:22 (2014)Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent., , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 391-407. PMLR, (2020)PREStO: A Systematic Framework for Blockchain Consensus Protocols., , and . IEEE Trans. Engineering Management, 67 (4): 1028-1044 (2020)Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System., and . AAMAS, page 233-241. International Foundation for Autonomous Agents and Multiagent Systems, (2019)Rethinking Blockchain Security: Position Paper., , , , , , , and . iThings/GreenCom/CPSCom/SmartData, page 1273-1280. IEEE, (2018)Game dynamics as the meaning of a game., and . SIGecom Exch., 16 (2): 53-63 (2018)First-order methods almost always avoid strict saddle points., , , , , and . Math. Program., 176 (1-2): 311-337 (2019)Incentives in Ethereum's hybrid Casper protocol., , , and . Int. J. Netw. Manag., (2020)