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margin maximization

49 papers

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Co-occurring keywords

support vector machine (978) gradient descent (1144) kernel methods (1097) implicit bia (107) semi-supervised learning (2341) generalization bound (652) perceptron algorithm (18) logistic regression (386) ensemble learning (1274) binary classification (678)

Papers

COMM: Concentrated Margin Maximization for Robust Document-Level Relation Extraction AAAI 2025
Expanding the Scope of Negatives: Boosting Image-Text Matching with Negatives Distribution Guided Learning AAAI 2025
Benign overfitting in leaky ReLU networks with moderate input dimension NIPS 2024
MICS: Midpoint Interpolation To Learn Compact and Separated Representations for Few-Shot Class-Incremental Learning WACV 2024
Multi-Class Support Vector Machine with Maximizing Minimum Margin AAAI 2024
The Implicit Bias of Adam on Separable Data NIPS 2024
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization COLT 2023
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability NIPS 2023
Faster Margin Maximization Rates for Generic Optimization Methods NIPS 2023
Margin-based Neural Network Watermarking ICML 2023
Domain Adaptation for Sentiment Analysis Using Robust Internal Representations EMNLP 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization NIPS 2023
Quantum perceptron revisited: Computational-statistical tradeoffs UAI 2022
Gradient Methods Provably Converge to Non-Robust Networks NIPS 2022
ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics AISTATS 2022
On Margin Maximization in Linear and ReLU Networks NIPS 2022
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias NIPS 2021
Fast margin maximization via dual acceleration ICML 2021
Narrow Margins: Classification, Margins and Fat Tails ICML 2021
Gradient descent follows the regularization path for general losses COLT 2020
Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization NIPS 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
Optimal Minimal Margin Maximization with Boosting ICML 2019
Multiclass Boosting: Margins, Codewords, Losses, and Algorithms JMLR 2019