margin maximization

Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias NeurIPS 2021 Narrow Margins: Classification, Margins and Fat Tails ICML 2021 Gradient descent follows the regularization path for general losses COLT 2020 Gradient Descent Maximizes the Margin of Homogeneous Neural Networks ICLR 2020 MMA Training: Direct Input Space Margin Maximization through Adversarial Training ICLR 2020 Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization NeurIPS 2020 The Performance Analysis of Generalized Margin Maximizers on Separable Data ICML 2020 Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models ICML 2019 Multiclass Boosting: Margins, Codewords, Losses, and Algorithms JMLR 2019 Optimal Minimal Margin Maximization with Boosting ICML 2019 Adversarial Metric Learning IJCAI 2018 Large Margin Neural Language Model EMNLP 2018 Multi-Class Support Vector Machine via Maximizing Multi-Class Margins IJCAI 2017 Large Margin Discriminant Dimensionality Reduction in Prediction Space NeurIPS 2016 Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs NeurIPS 2016 Feature Selection for Linear SVM with Provable Guarantees AISTATS 2015 Margins, Kernels and Non-linear Smoothed Perceptrons ICML 2014 Direct 0-1 Loss Minimization and Margin Maximization with Boosting NeurIPS 2013 Random Projections for Support Vector Machines AISTATS 2013 Learning Kernels with Radiuses of Minimum Enclosing Balls NeurIPS 2010 Maximum Relative Margin and Data-Dependent Regularization JMLR 2010 Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010 Max-margin Classification of Data with Absent Features JMLR 2008 Optimization Techniques for Semi-Supervised Support Vector Machines JMLR 2008 Relative Margin Machines NeurIPS 2008