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]

'Exogenous Randomness Empowering Random Forests', by Tianxing Mei, Yingying Fan, Jinchi Lv. jmlr.org/papers/v27/25-0247.… #forests #trees #tree

'Kernel Mean Embedding Deviation Subspace for Unsupervised Learning with Heterogeneous Data', by Luoyao Yu, Lixing Zhu, Ruoqing Zhu, Xuehu Zhu. jmlr.org/papers/v27/25-0163.… #clustering #dimensional #embedding

'Deep Nonparametric Conditional Independence Tests for Images', by Marco Simnacher, Xiangnan Xu, Hani Park, Christoph Lippert, Sonja Greven. jmlr.org/papers/v27/25-0107.… #confounders #confounder #embedding

'Semi-supervised learning for linear extremile regression', by Rong Jiang, Jiangfeng Wang, Keming Yu. jmlr.org/papers/v27/25-0093.… #regression #nonparametric #quantile

'Transfer Learning via Regularized Random-effects Linear Discriminant Analysis', by Hongzhe Zhang, Arnab Auddy, Hongzhe Li. jmlr.org/papers/v27/25-0031.… #discriminant #classification #predictors

'Cheap Bootstrap for Fast Uncertainty Quantification of Stochastic Gradient Descent', by Henry Lam, Zitong Wang. jmlr.org/papers/v27/25-0008.… #sgd #resampling #sgds

'A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equation', by Shu Liu, Stanley Osher, Wuchen Li. jmlr.org/papers/v27/24-1929.… #gradient #optimizer #optimization

'Generalized Resubstitution for Regression Error Estimation', by Diego Marcondes, Ulisses Braga-Neto. jmlr.org/papers/v27/24-1905.… #estimators #estimator #regression

'Transfer Conformal Predictive Inference for Regression', by Ce Zhang, Ting Li, Jinhan Xie, Linglong Kong, Bei Jiang. jmlr.org/papers/v27/24-1899.… #prediction #regression #datasets

'Towards Convexity in Anomaly Detection: A New Formulation of SSLM with Unique Optimal Solutions', by Hongying Liu, Hao Wang, Haoran Chu, Yibo Wu. jmlr.org/papers/v27/24-1885.… #svms #svm #hyperparameters

'Node Regression on Latent Position Random Graphs via Local Averaging', by Martin Gjorgjevski, Nicolas Keriven, Simon Barthelme, Yohann De Castro. jmlr.org/papers/v27/24-1819.… #nodes #neighboring #node

'On the Relevance of Byzantine Robust Optimization Against Data Poisoning', by Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot. jmlr.org/papers/v27/24-1748.… #robustness #faults #datasets

'Best Arm Identification with Minimal Regret', by Junwen Yang, Vincent Y. F. Tan, Tianyuan Jin. jmlr.org/papers/v27/24-1612.… #bandit #regret #optimality

'Convergence of Noise-Free Sampling Algorithms with Regularized Wasserstein Proximals', by Fuqun Han, Stanley Osher, Wuchen Li. jmlr.org/papers/v27/24-1560.… #langevin #wasserstein #planck

'Almost Sure Convergence of Linear Temporal Difference Learning with Arbitrary Features', by Jiuqi Wang, Shangtong Zhang. jmlr.org/papers/v27/24-1538.… #reinforcement #prediction #approximation

'Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models', by Jiaqi Li, Johannes Schmidt-Hieber, Wei Biao Wu. jmlr.org/papers/v27/24-1484.… #sgd #dropout #asgd

'Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data', by Wanli Hong, Shuyang Ling. jmlr.org/papers/v27/24-1429.… #depth #deep #features

'Differentially Private Estimation and Inference in High-Dimensional Regression with FDR Control', by Zhanrui Cai, Sai Li, Xintao Xia, Linjun Zhang. jmlr.org/papers/v27/24-1413.… #privacy #private #predictors

'Demographic Parity in Regression and Classification Within the Unawareness Framework', by Vincent Divol, Solenne Gaucher. jmlr.org/papers/v27/24-1338.… #classifiers #classification #optimal

'Enhancing Accuracy in Generative Models via Knowledge Transfer', by Xinyu Tian, Xiaotong Shen. jmlr.org/papers/v27/24-1291.… #generative #leveraging #knowledge