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#estimators — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #estimators, aggregated by home.social.

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

    jmlr.org/papers/v26/24-0060.ht

    #estimation #estimators #estimator

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

    jmlr.org/papers/v25/23-1405.ht

    #adversarial #estimators #regularized

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

    jmlr.org/papers/v25/23-1405.ht

    #adversarial #estimators #regularized

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

    jmlr.org/papers/v25/23-1405.ht

    #adversarial #estimators #regularized

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

    jmlr.org/papers/v25/23-1405.ht

    #adversarial #estimators #regularized

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

    jmlr.org/papers/v25/23-0063.ht

    #rademacher #estimators #estimator

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

    jmlr.org/papers/v25/23-1077.ht

    #estimates #causal #estimators

  8. '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.

    jmlr.org/papers/v25/22-1124.ht

    #lasso #semiparametric #estimators

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

    jmlr.org/papers/v25/23-0918.ht

    #nonparametric #estimators #minimax

  10. 'Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning', by Yiling Xie, Xiaoming Huo.

    jmlr.org/papers/v25/23-0379.ht

    #wasserstein #estimators #robust

  11. 'On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators', by Zejian Liu, Meng Li.

    jmlr.org/papers/v24/21-1110.ht

    #estimation #estimators #nonparametric

  12. 'Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption', by Lihu Xu, Fang Yao, Qiuran Yao, Huiming Zhang.

    jmlr.org/papers/v24/22-0034.ht

    #estimators #estimator #estimations