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-…

#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-…

#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-…

#confounders #confounder #embedding

'Semi-supervised learning for linear extremile regression', by Rong Jiang, Jiangfeng Wang, Keming Yu.

jmlr.org/papers/v27/25-…

#regression #nonparametric #quantile

'Transfer Learning via Regularized Random-effects Linear Discriminant Analysis', by Hongzhe Zhang, Arnab Auddy, Hongzhe Li.

jmlr.org/papers/v27/25-…

#discriminant #classification #predictors

'Cheap Bootstrap for Fast Uncertainty Quantification of Stochastic Gradient Descent', by Henry Lam, Zitong Wang.

jmlr.org/papers/v27/25-…

#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-…

#gradient #optimizer #optimization

'Generalized Resubstitution for Regression Error Estimation', by Diego Marcondes, Ulisses Braga-Neto.

jmlr.org/papers/v27/24-…

#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-…

#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-…

#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-…

#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-…

#robustness #faults #datasets

'Best Arm Identification with Minimal Regret', by Junwen Yang, Vincent Y. F. Tan, Tianyuan Jin.

jmlr.org/papers/v27/24-…

#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-…

#langevin #wasserstein #planck

'Almost Sure Convergence of Linear Temporal Difference Learning with Arbitrary Features', by Jiuqi Wang, Shangtong Zhang.

jmlr.org/papers/v27/24-…

#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-…

#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-…

#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-…

#privacy #private #predictors

'Demographic Parity in Regression and Classification Within the Unawareness Framework', by Vincent Divol, Solenne Gaucher.

jmlr.org/papers/v27/24-…

#classifiers #classification #optimal

'Enhancing Accuracy in Generative Models via Knowledge Transfer', by Xinyu Tian, Xiaotong Shen.

jmlr.org/papers/v27/24-…

#generative #leveraging #knowledge