Regularization

Dynamically Refined Regularization for Improving Cross-corpora Hate Speech Detection ACL 2022 GA-SAM: Gradient-Strength based Adaptive Sharpness-Aware Minimization for Improved Generalization EMNLP 2022 Improving Neural Political Statement Classification with Class Hierarchical Information ACL 2022 In Defense of the Unitary Scalarization for Deep Multi-Task Learning NeurIPS 2022 Noisy Label Regularisation for Textual Regression COLING 2022 On Mixup Regularization JMLR 2022 On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity NeurIPS 2022 PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks AAAI 2022 Prediction Difference Regularization against Perturbation for Neural Machine Translation ACL 2022 Robust computation of optimal transport by $β$-potential regularization ACML 2022 STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing EMNLP 2022 The Implicit Delta Method NeurIPS 2022 Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints NeurIPS 2022 To Smooth or Not? When Label Smoothing Meets Noisy Labels ICML 2022 Wind Prediction under Random Data Corruption (Student Abstract) AAAI 2022 Adaptive Knowledge Driven Regularization for Deep Neural Networks AAAI 2021 A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization AAAI 2021 AutoDropout: Learning Dropout Patterns to Regularize Deep Networks AAAI 2021 From Label Smoothing to Label Relaxation AAAI 2021 How Does Mixup Help With Robustness and Generalization? ICLR 2021 Implicit Regularization in Matrix Sensing via Mirror Descent NeurIPS 2021 Implicit Regularization in ReLU Networks with the Square Loss COLT 2021 Interpolation can hurt robust generalization even when there is no noise NeurIPS 2021 Kernel-convoluted Deep Neural Networks with Data Augmentation AAAI 2021 Learning the optimal Tikhonov regularizer for inverse problems NeurIPS 2021