mean squared error

Least Squares Model Averaging for Distributed Data JMLR 2023 Minimum-Risk Recalibration of Classifiers NeurIPS 2023 Mixed Linear Regression via Approximate Message Passing AISTATS 2023 On the choice of Perception Loss Function for Learned Video Compression NeurIPS 2023 On the Statistical Benefits of Temporal Difference Learning ICML 2023 Revisiting Bellman Errors for Offline Model Selection ICML 2023 Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms JMLR 2022 Convergence Guarantees for the Good-Turing Estimator JMLR 2022 Crowdsourcing Regression: A Spectral Approach AISTATS 2022 Differential privacy for symmetric log-concave mechanisms AISTATS 2022 Fundamental limits for rank-one matrix estimation with groupwise heteroskedasticity AISTATS 2022 Generalizing Gaussian Smoothing for Random Search ICML 2022 Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs NeurIPS 2022 Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path ICLR 2022 Online Balanced Experimental Design ICML 2022 Quantile regression with ReLU Networks: Estimators and minimax rates JMLR 2022 Scaling Laws from the Data Manifold Dimension JMLR 2022 The Correlation-assisted Missing Data Estimator JMLR 2022 A Theory of the Distortion-Perception Tradeoff in Wasserstein Space NeurIPS 2021 Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation IJCAI 2021 Error-Sensitive Evaluation for Ordinal Target Variables EMNLP 2021 Expected Validation Performance and Estimation of a Random Variable’s Maximum EMNLP 2021 High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding AISTATS 2021 Learning the optimal Tikhonov regularizer for inverse problems NeurIPS 2021 On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework ICML 2021