model selection

Identifying a Minimal Class of Models for High--dimensional Data JMLR 2017 LIMSI@CoNLL’17: UD Shared Task CoNLL 2017 Locally Consistent Bayesian Network Scores for Multi-Relational Data IJCAI 2017 Nonparametric Online Machine Learning with Kernels IJCAI 2017 Parameter-Free Online Learning via Model Selection NeurIPS 2017 Scalable Model Selection for Belief Networks NeurIPS 2017 Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction NeurIPS 2017 Universality of Bayesian mixture predictors ALT 2017 Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications ACML 2017 A Brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning Without Human Intervention AutoML 2016 A Consistent Information Criterion for Support Vector Machines in Diverging Model Spaces JMLR 2016 Active Nearest-Neighbor Learning in Metric Spaces NeurIPS 2016 A DNN-HMM Approach to Non-Negative Matrix Factorization Based Speech Enhancement Interspeech 2016 Bayesian optimization for automated model selection NeurIPS 2016 Bayesian optimization for automated model selection AutoML 2016 Blockout: Dynamic Model Selection for Hierarchical Deep Networks CVPR 2016 Boosting for Efficient Model Selection for Syntactic Parsing COLING 2016 Choice of V for V-Fold Cross-Validation in Least-Squares Density Estimation JMLR 2016 Enhancing Multilingual Recognition of Emotion in Speech by Language Identification Interspeech 2016 Guarding against Spurious Discoveries in High Dimensions JMLR 2016 Hyperparameter optimization with approximate gradient ICML 2016 Learning to Select Pre-Trained Deep Representations With Bayesian Evidence Framework CVPR 2016 mlr: Machine Learning in R JMLR 2016 Multiple Model Fitting as a Set Coverage Problem CVPR 2016 No penalty no tears: Least squares in high-dimensional linear models ICML 2016