Machine Learning & AI
At the forefront of technological innovation, Machine Learning involves crafting algorithms for autonomous learning, while AI simulates human intelligence. Integrating multi-agent systems and game theory enhances decision-making in complex environments, finding applications in finance, cybersecurity, and resource management.
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68 result(s)
Online Algorithms for the Maximum k-interval Coverage Problem
S. Li, M. Li, L. Duan, V. C.S. Lee, 2022, Journal of Combinatorial Optimization (JOCO), 44, 3364–3404, https://arxiv.org/abs/2011.10938
Optimal Transport-Based Distributionally Robust Optimization: Structural Properties and Iterative Schemes
J. Blanchet, K. Murthy, F. Zhang, 2022, Mathematics of Operations Research, (47) 2, 1500-1529, https://pubsonline.informs.org/doi/abs/10.1287/moor.2021.1178
Parallel k-clique Counting on GPUs
M Almasri, IE Hajj, R Nagi, J Xiong, W Hwu, 2022, Proceedings of the 36th ACM International Conference on Supercomputing, 10-14, https://dl.acm.org/doi/pdf/10.1145/3524059.3532382
Protecting Location Privacy by Multi-query: A Dynamic Bayesian Game Theoretic Approach
S. Hong, L. Duan, and J. Huang, 2022, IEEE Transactions on Information Forensics & Security (TIFS), 17, 2569 – 2584, http://people.sutd.edu.sg/~lingjie_duan/wp-content/uploads/2022/07/TIFS_PrivacyGame.pdf
Support Vector Machines as Bayes' Classifiers
P. Jackson, 2022, Operations Research Letters, 50, No. 5, Sept. 2022, 423-429
To Help or Disturb: Introduction of Crowdsourced WiFi to 5G Networks
S. Hao and L. Duan, 2022, IEEE Transactions on Mobile Computing, 22(9), 5583 – 5596, https://arxiv.org/abs/2206.08261
A Cost–based Analysis for Risk-averse Explore-then-commit Finite-time Bandits
A Yekkehkhany, E Arian, R Nagi, I Shomorony , 2021, IISE Transactions, Volume 53, Issue 10, 1094-1108, https://www.tandfonline.com/doi/pdf/10.1080/24725854.2021.1882014
Analysis of optimization algorithms via sum-of-squares
S. S.Y. Tan , V. Y.F. Tan, A Varvitsiotis, 2021, Journal of Optimization Theory and Applications, https://link.springer.com/article/10.1007/s10957-021-01869-0?fbclid=IwAR3ODcpJfH4ByBOTmartQi_Ew_4zLEL4mTsuE8XFjrTukSRi1KHc2nA8pkE
Comparison of Semantic Segmentation Deep Learning Models for Land Use Mapping: Site Characterization for Construction Site Preparation
AM Lobato, M Juston, WR Norris, R Nagi, A Soylemezoglu, D Nottage, 2021, IIE Annual Conference. Proceedings, 1142-1147
Determinantal Point Processes Based on Orthogonal Polynomials for Sampling Minibatches in SGD
R. Bardenet, S. Ghosh, and M. Lin, 2021, Conference on Neural Information Processing Systems (NeurIPS), https://proceedings.neurips.cc/paper/2021/file/8744cf92c88433f8cb04a02e6db69a0d-Paper.pdf