generalization error bound

Generalization error bounds for deep unfolding RNNs UAI 2021 Graph-based semi-supervised learning through the lens of safety UAI 2021 Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation ICML 2021 Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks AAAI 2021 On the Provable Generalization of Recurrent Neural Networks NeurIPS 2021 Parameter-free HE-friendly Logistic Regression NeurIPS 2021 Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization NeurIPS 2021 Adaptive Adversarial Multi-task Representation Learning ICML 2020 A Distance-Weighted Class-Homogeneous Neighbourhood Ratio for Algorithm Selection ACML 2020 A One-step Approach to Covariate Shift Adaptation ACML 2020 Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network ICLR 2020 Deep Streaming Label Learning ICML 2020 Generalization Error Bounds of Gradient Descent for Learning Over-Parameterized Deep ReLU Networks AAAI 2020 Learning from Label Proportions: A Mutual Contamination Framework NeurIPS 2020 Learning Stability Certificates from Data CoRL 2020 On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning ICLR 2020 Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020 Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm IJCAI 2019 Multi-class Heterogeneous Domain Adaptation JMLR 2019 On Robustness of Principal Component Regression NeurIPS 2019 Unsupervised Domain Adaptation Based on Source-Guided Discrepancy AAAI 2019 Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds AAAI 2019 Fast generalization error bound of deep learning from a kernel perspective AISTATS 2018 Learning Deep ResNet Blocks Sequentially using Boosting Theory ICML 2018 Learning From Noisy Singly-labeled Data ICLR 2018