Additionally, crew duty constraints, passenger reassignment, and interrelated infection propagation factors are newly incorporated using the distributionally robust optimization approach to model uncertainty in the transmission probability. In this section, the complete nonlinear model is first presented then it...
Multi-stage fully adaptive distributionally robust unit commitment for power system based on mixed approximation rules Mao Liu, Xiangyu Kong, Chao Ma, Xuesong Zhou, Qingxiang Lin Article 124051 select article Electrochemical model boosting accurate prediction of calendar life for commercial LiFePO<sub>4...
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm 2023 NeurIPS FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning 2023 NeurIPS Distributionally Robust Memory Evolution with Generalized Divergence for Continual Learning 2023 TPAMI Improvin...
2020-05-27 Learning LWF Chain Graphs: an Order Independent Algorithm Abstract | PDF 2020-05-26 Towards intervention-centric causal reasoning in learning agents Abstract | PDF 2020-05-26 Analysis of the Penn Korean Universal Dependency Treebank (PKT-UD): Manual Revision to Build Robust Parsing...
Hybrid turbine MPPT HESS: Hybrid energy storage systems GA: Genetic Algorithm GP: Gained power (W) LCA: Life Cycle Assesment LCOE: Levelized Cost Of Energy MPPT: Maximum power point tracking OTC: Optimal Torque Control PMC: Power management control...
such as urgency levels, weather conditions, and resource availability. By leveraging advanced machine learning techniques, particularly Gradient Boosting models, the research offers a nuanced understanding of how these factors interact and provides a robust framework for predictive analytics in EMS ...
The datasets include color variations, synthetic data, and types of corruption stochastic gradient descent (SGD) algorithm with a learning rate of 3e-2. We applied the same configuration for training the source model on CIFAR-100, extending the training to 16,000 iterations with a warm-up ...
COCO-DR: Combating distribution shifts in zero-shot dense retrieval with contrastive and distributionally robust learning. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022. [59] Yue Yu, Yuchen Zhuang, Rongzhi Zhang, Yu Meng, Jiaming Shen, and Chao...
Further, the second-order cone relaxing (SOCR) method and the hybrid gray wolf optimal and particle swarm optimal (GWO-PSO) algorithm are applied to solve the optimization model. Using MATLAB, the modified IEEE 33-node and 118-node systems are built to check the proposed approach's ...
2020-05-27 Learning LWF Chain Graphs: an Order Independent Algorithm Abstract | PDF 2020-05-26 Towards intervention-centric causal reasoning in learning agents Abstract | PDF 2020-05-26 Analysis of the Penn Korean Universal Dependency Treebank (PKT-UD): Manual Revision to Build Robust Parsing...