high-dimensional data

Clustering High Dimensional Dynamic Data Streams ICML 2017 Identifying a Minimal Class of Models for High--dimensional Data JMLR 2017 Minimax Filter: Learning to Preserve Privacy from Inference Attacks JMLR 2017 Multiscale Quantization for Fast Similarity Search NeurIPS 2017 Practical Data-Dependent Metric Compression with Provable Guarantees NeurIPS 2017 Product Split Trees CVPR 2017 Robust Discriminative Clustering with Sparse Regularizers JMLR 2017 Semi-supervised Feature Selection via Rescaled Linear Regression IJCAI 2017 Single-Pass PCA of Large High-Dimensional Data IJCAI 2017 SVD-Based Screening for the Graphical Lasso IJCAI 2017 The Role of Textualisation and Argumentation in Understanding the Machine Learning Process IJCAI 2017 Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data ICML 2017 Active Learning Algorithms for Graphical Model Selection AISTATS 2016 Adaptive Lasso and group-Lasso for functional Poisson regression JMLR 2016 Bayesian group factor analysis with structured sparsity JMLR 2016 Clustering High Dimensional Categorical Data via Topographical Features ICML 2016 CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data JMLR 2016 Feature-distributed sparse regression: a screen-and-clean approach NeurIPS 2016 Finding significant combinations of features in the presence of categorical covariates NeurIPS 2016 Higher-Order Factorization Machines NeurIPS 2016 Model-free Variable Selection in Reproducing Kernel Hilbert Space JMLR 2016 Computationally Bounded Retrieval CVPR 2015 Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures AISTATS 2015 Learning Efficient Anomaly Detectors from K-NN Graphs AISTATS 2015 On the consistency theory of high dimensional variable screening NeurIPS 2015