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Generalization Bounds

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TitleStatusHype
The Landscape of Deep Learning Algorithms—0
Mass Volume Curves and Anomaly Ranking—0
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training DataCode0
On the benefits of output sparsity for multi-label classification—0
Data-Dependent Stability of Stochastic Gradient Descent—0
A Theory of Output-Side Unsupervised Domain Adaptation—0
Learning Kernels with Random Features—0
Generalization Bounds for Weighted Automata—0
Kernel Ridge Regression via Partitioning—0
Distribution-dependent concentration inequalities for tighter generalization bounds—0
Multi-task and Lifelong Learning of Kernels—0
The Structured Weighted Violations Perceptron Algorithm—0
Loss factorization, weakly supervised learning and label noise robustness—0
Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes—0
Foundations of Coupled Nonlinear Dimensionality Reduction—0
A study of the classification of low-dimensional data with supervised manifold learning—0
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms—0
On the accuracy of self-normalized log-linear models—0
Random Maxout Features—0
When and why are log-linear models self-normalizing?—0
Towards a Learning Theory of Cause-Effect InferenceCode0
(Almost) No Label No Cry—0
Task-group Relatedness and Generalization Bounds for Regularized Multi-task Learning—0
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality—0
Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side KnowledgeCode0
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