Summary of Improving Demand Forecasting in Open Systems with Cartogram-enhanced Deep Learning, by Sangjoon Park et al.
Improving Demand Forecasting in Open Systems with Cartogram-Enhanced Deep Learningby Sangjoon Park, Yongsung Kwon, Hyungjoon…
Improving Demand Forecasting in Open Systems with Cartogram-Enhanced Deep Learningby Sangjoon Park, Yongsung Kwon, Hyungjoon…
Manifold Regularization Classification Model Based On Improved Diffusion Mapby Hongfu Guo, Wencheng Zou, Zeyu Zhang,…
IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution Historyby Yi Xu, Weiran Shen, Xiao…
Data-centric Prediction Explanation via Kernelized Stein Discrepancyby Mahtab Sarvmaili, Hassan Sajjad, Ga WuFirst submitted to…
FairerCLIP: Debiasing CLIP’s Zero-Shot Predictions using Functions in RKHSsby Sepehr Dehdashtian, Lan Wang, Vishnu Naresh…
Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalizationby Khiem Le, Long Ho, Cuong…
Parametric Encoding with Attention and Convolution Mitigate Spectral Bias of Neural Partial Differential Equation Solversby…
EAGLE: A Domain Generalization Framework for AI-generated Text Detectionby Amrita Bhattacharjee, Raha Moraffah, Joshua Garland,…
Group Benefits Instances Selection for Data Purificationby Zhenhuang Cai, Chuanyi Zhang, Dan Huang, Yuanbo Chen,…
The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneityby Tongle Wu, Zhize Li,…