Luo Luo
Orcid: 0009-0000-3641-8992
According to our database1,
Luo Luo
authored at least 53 papers
between 2008 and 2024.
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Bibliography
2024
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Decentralized Gradient-Free Methods for Stochastic Non-smooth Non-convex Optimization.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
J. Mach. Learn. Res., 2023
Faster Stochastic Algorithms for Minimax Optimization under Polyak-Łojasiewicz Conditions.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
A Simple and Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization.
CoRR, 2022
CoRR, 2022
Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization.
CoRR, 2022
Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Partial-Quasi-Newton Methods: Efficient Algorithms for Minimax Optimization Problems with Unbalanced Dimensionality.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
2021
IEEE Trans. Neural Networks Learn. Syst., 2021
Finding Second-Order Stationary Point for Nonconvex-Strongly-Concave Minimax Problem.
CoRR, 2021
Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization.
CoRR, 2021
Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Pattern Recognit., 2019
J. Mach. Learn. Res., 2019
CoRR, 2019
2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
2017
CoRR, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions.
J. Mach. Learn. Res., 2016
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
Frequent Direction Algorithms for Approximate Matrix Multiplication with Applications in CCA.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016
2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
2013
Proceedings of the 2013 IEEE International Conference on Big Data (IEEE BigData 2013), 2013
2008
Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education, 2008