mean squared error

Towards a Mechanistic Explanation of Diffusion Model Generalization ICML 2025 Unbiased Quantization of the L_1 Ball for Communication-Efficient Distributed Mean Estimation AISTATS 2025 Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning JMLR 2024 Data-Efficient Policy Evaluation Through Behavior Policy Search JMLR 2024 Denoising Autoregressive Representation Learning ICML 2024 FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning ECCV 2024 Fundamental Limits of Non-Linear Low-Rank Matrix Estimation COLT 2024 How to Train the Teacher Model for Effective Knowledge Distillation ECCV 2024 Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies ICLR 2024 Learning Under Random Distributional Shifts AISTATS 2024 NLP-LISAC at SemEval-2024 Task 1: Transformer-based approaches for Determining Semantic Textual Relatedness SemEval 2024 Only Strict Saddles in the Energy Landscape of Predictive Coding Networks? NeurIPS 2024 Precise Model Benchmarking with Only a Few Observations EMNLP 2024 Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages ICML 2024 Proportion-based Sensitivity Analysis of Uncontrolled Confounding Bias in Causal Inference IJCAI 2024 Regularized Q-learning through Robust Averaging ICML 2024 The Solution Path of SLOPE AISTATS 2024 Transformers can optimally learn regression mixture models ICLR 2024 Balanced Off-Policy Evaluation for Personalized Pricing AISTATS 2023 Distributed Statistical Inference under Heterogeneity JMLR 2023 Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence JMLR 2023 Evaluating Unsupervised Denoising Requires Unsupervised Metrics ICML 2023 High-dimensional Asymptotics of Denoising Autoencoders NeurIPS 2023 Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks JMLR 2023 Improving Deep Regression with Ordinal Entropy ICLR 2023