'Sampling and Estimation on Manifolds using the Langevin Diffusion', by Karthik Bharath, Alexander Lewis, Akash Sharma, Michael V. Tretyakov.

http://jmlr.org/papers/v26/24-0829.html

#estimation #langevin #estimators

Sampling and Estimation on Manifolds using the Langevin Diffusion

'Instability, Computational Efficiency and Statistical Accuracy', by Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu.

http://jmlr.org/papers/v26/22-0300.html

#estimation #estimators #algorithms

Instability, Computational Efficiency and Statistical Accuracy

'Error estimation and adaptive tuning for unregularized robust M-estimator', by Pierre C. Bellec, Takuya Koriyama.

http://jmlr.org/papers/v26/24-0060.html

#estimation #estimators #estimator

Error estimation and adaptive tuning for unregularized robust M-estimator

'Locally Private Causal Inference for Randomized Experiments', by Yuki Ohnishi, Jordan Awan.

http://jmlr.org/papers/v26/23-1401.html

#privacy #private #estimators

Locally Private Causal Inference for Randomized Experiments

'Learning with a linear loss function: excess risk and estimation bound..."', by Guillaume Lecué, Lucie Neirac.

http://jmlr.org/papers/v25/23-1405.html

#adversarial #estimators #regularized

Learning with a linear loss function: excess risk and estimation bounds for ERM, minmax MOM and their regularized versions with applications to robustness in sparse PCA.

'Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition', by Varun Kanade, Patrick Rebeschini, Tomas Vaskevicius.

http://jmlr.org/papers/v25/23-0063.html

#rademacher #estimators #estimator

Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition

'Causal effects of intervening variables in settings with unmeasured confounding', by Lan Wen, Aaron Sarvet, Mats Stensrud.

http://jmlr.org/papers/v25/23-1077.html

#estimates #causal #estimators

Causal effects of intervening variables in settings with unmeasured confounding

'Inference on High-dimensional Single-index Models with Streaming Data', by Dongxiao Han, Jinhan Xie, Jin Liu, Liuquan Sun, Jian Huang, Bei Jiang, Linglong Kong.

http://jmlr.org/papers/v25/22-1124.html

#lasso #semiparametric #estimators

Inference on High-dimensional Single-index Models with Streaming Data

'Stability and L2-penalty in Model Averaging', by Hengkun Zhu, Guohua Zou.

http://jmlr.org/papers/v25/23-0853.html

#averaging #estimators #models

Stability and L2-penalty in Model Averaging

'Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks', by Yunfei Yang, Ding-Xuan Zhou.

http://jmlr.org/papers/v25/23-0918.html

#nonparametric #estimators #minimax

Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks