JMLR has recently launched a Special Issue on ML for addressing problems of climate change! We welcome all submissions which use machine learning to address problems of climate change, including mitigation, adaptation, and climate science. [1/4]
'Contrasting Local and Global Modeling with Machine Learning and Satellite Data: A Case Study Estimating Tree Canopy Height in African Savannas', by Esther Rolf, Lucia Gordon, Milind Tambe, Andrew Davies.
jmlr.org/papers/v27/24-1592.…#geospatial#regions#glob
'A causal fused lasso for interpretable heterogeneous treatment effects estimation', by Oscar Hernan Madrid Padilla, Yanzhen Chen, Carlos Misael Madrid Padilla, Gabriel Ruiz.
jmlr.org/papers/v27/23-0535.…#lasso#covariates#propensity
'Reparameterized Complex-valued Neurons Can Efficiently Learn More than Real-valued Neurons via Gradient Descent', by Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou.
jmlr.org/papers/v27/25-1106.…#neuron#complex#learns