square loss

Nearly Optimal Sample Complexity for Learning with Label Proportions ICML 2025 Efficiently Learning One-Hidden-Layer ReLU Networks via SchurPolynomials COLT 2024 On the Performance of Empirical Risk Minimization with Smoothed Data COLT 2024 Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss ICML 2024 Cut your Losses with Squentropy ICML 2023 Regression as Classification: Influence of Task Formulation on Neural Network Features AISTATS 2023 Understanding Square Loss in Training Overparametrized Neural Network Classifiers NeurIPS 2022 Direct Loss Minimization for Sparse Gaussian Processes AISTATS 2021 EVALUATION OF NEURAL ARCHITECTURES TRAINED WITH SQUARE LOSS VS CROSS-ENTROPY IN CLASSIFICATION TASKS ICLR 2021 Implicit Regularization in ReLU Networks with the Square Loss COLT 2021 Approximation Schemes for ReLU Regression COLT 2020 Does data interpolation contradict statistical optimality? AISTATS 2019 Sum-of-squares meets square loss: Fast rates for agnostic tensor completion COLT 2019 Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals NeurIPS 2019 Uniform regret bounds over R^d for the sequential linear regression problem with the square loss ALT 2019 Kernel Square-Loss Exemplar Machines for Image Retrieval CVPR 2017 Online Sparse Linear Regression COLT 2016 On Regularizing Rademacher Observation Losses NeurIPS 2016 Optimal Learning for Multi-pass Stochastic Gradient Methods NeurIPS 2016 Minimax Time Series Prediction NeurIPS 2015 Efficient Minimax Strategies for Square Loss Games NeurIPS 2014 Beyond Logarithmic Bounds in Online Learning AISTATS 2012