generalization performance

Towards Better Generalization of Adaptive Gradient Methods NeurIPS 2020 Understanding Architectures Learnt by Cell-based Neural Architecture Search ICLR 2020 VECA: A Method for Detecting Overfitting in Neural Networks (Student Abstract) AAAI 2020 An Empirical Study of Example Forgetting during Deep Neural Network Learning ICLR 2019 Asymmetric Valleys: Beyond Sharp and Flat Local Minima NeurIPS 2019 Data-Distortion Guided Self-Distillation for Deep Neural Networks AAAI 2019 Decoupled Weight Decay Regularization ICLR 2019 How to train your MAML ICLR 2019 Improving Model Selection by Employing the Test Data ICML 2019 Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin AAAI 2019 Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation AISTATS 2019 Regularizing Neural Networks via Stochastic Branch Layers ACML 2019 Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets ACL 2019 There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average ICLR 2019 Towards Reliable Learning for High Stakes Applications AAAI 2019 Feature Quantization for Defending Against Distortion of Images CVPR 2018 Gradient Diversity: a Key Ingredient for Scalable Distributed Learning AISTATS 2018 Improved Expressivity Through Dendritic Neural Networks NeurIPS 2018 Learning Compact Neural Networks with Regularization ICML 2018 On the importance of single directions for generalization ICLR 2018 Supervised autoencoders: Improving generalization performance with unsupervised regularizers NeurIPS 2018 The Effect of Network Width on the Performance of Large-batch Training NeurIPS 2018 Asymptotic behavior of Support Vector Machine for spiked population model JMLR 2017 Multi-Class Optimal Margin Distribution Machine ICML 2017 The Marginal Value of Adaptive Gradient Methods in Machine Learning NeurIPS 2017