hinge loss

Benign overfitting in leaky ReLU networks with moderate input dimension NeurIPS 2024 MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations ICML 2024 The Nyström method for convex loss functions JMLR 2024 Adaptive Hinge Balance Loss for Document-Level Relation Extraction EMNLP 2023 Improved Kernel Alignment Regret Bound for Online Kernel Learning AAAI 2023 The Implicit Bias of Benign Overfitting JMLR 2023 Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? NeurIPS 2023 Agnostic Learnability of Halfspaces via Logistic Loss ICML 2022 Improved Classification Rates for Localized SVMs JMLR 2022 Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation JMLR 2022 Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification ICML 2022 Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization CVPR 2021 A Multi-Class Hinge Loss for Conditional GANs WACV 2021 Coresets for Classification – Simplified and Strengthened NeurIPS 2021 An analytic theory of shallow networks dynamics for hinge loss classification NeurIPS 2020 On the Error Resistance of Hinge-Loss Minimization NeurIPS 2020 Weston-Watkins Hinge Loss and Ordered Partitions NeurIPS 2020 Clipped Matrix Completion: A Remedy for Ceiling Effects AAAI 2019 Learning Weighted Top-k Support Vector Machine ACML 2019 Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations ALT 2019 Versatile Multiple Choice Learning and Its Application to Vision Computing CVPR 2019 Hinge-Minimax Learner for the Ensemble of Hyperplanes JMLR 2018 Understanding the Loss Surface of Neural Networks for Binary Classification ICML 2018 Adversarial Surrogate Losses for Ordinal Regression NeurIPS 2017 Approximation Vector Machines for Large-scale Online Learning JMLR 2017