model selection

Joint Inference for Neural Network Depth and Dropout Regularization NeurIPS 2021 Learning Curves for Analysis of Deep Networks ICML 2021 LogME: Practical Assessment of Pre-trained Models for Transfer Learning ICML 2021 Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models JMLR 2021 Model Linkage Selection for Cooperative Learning JMLR 2021 Model Selection for Bayesian Autoencoders NeurIPS 2021 Model Selection for Cross-lingual Transfer EMNLP 2021 Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings MLHC 2021 MultiLink: Multi-Class Structure Recovery via Agglomerative Clustering and Model Selection CVPR 2021 Non-parametric Quantile Regression via the K-NN Fused Lasso JMLR 2021 Offline detection of change-points in the mean for stationary graph signals. AISTATS 2021 Online Active Model Selection for Pre-trained Classifiers AISTATS 2021 Online Model Selection for Reinforcement Learning with Function Approximation AISTATS 2021 Predicting Deep Neural Network Generalization with Perturbation Response Curves NeurIPS 2021 Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond JMLR 2021 Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits AISTATS 2021 Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels AAAI 2021 Scalable Diverse Model Selection for Accessible Transfer Learning NeurIPS 2021 Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning ICML 2021 Sequential prediction under log-loss and misspecification COLT 2021 The Pareto Frontier of model selection for general Contextual Bandits NeurIPS 2021 Tighter Risk Certificates for Neural Networks JMLR 2021 True Few-Shot Learning with Language Models NeurIPS 2021 Unsupervised Multi-Source Domain Adaptation Without Access to Source Data CVPR 2021 We Need to Talk About train-dev-test Splits EMNLP 2021