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Statistical Learning

4076 directly classified papers

Papers per year

Papers

Detecting and Correcting for Label Shift with Black Box Predictors ICML 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates ICML 2018
Emergence of Invariance and Disentanglement in Deep Representations JMLR 2018
Privacy-preserving Prediction COLT 2018
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions ICML 2018
Goodness-of-Fit Tests for Random Partitions via Symmetric Polynomials JMLR 2018
Near-Optimal Sample Complexity Bounds for Maximum Likelihood Estimation of Multivariate Log-concave Densities COLT 2018
Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression COLT 2018
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data ICML 2018
Informative Features for Model Comparison NIPS 2018
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning JMLR 2018
Orthogonal Machine Learning: Power and Limitations ICML 2018
Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features NIPS 2018
Revealing Common Statistical Behaviors in Heterogeneous Populations ICML 2018
Topological mixture estimation ICML 2018
Is ATIS Too Shallow to Go Deeper for Benchmarking Spoken Language Understanding Models? INTERSPEECH 2018
The Role of Temporal Variation in Narrative Organization INTERSPEECH 2018
On the Stability of Feature Selection Algorithms JMLR 2018
Group Invariance Principles for Causal Generative Models AISTATS 2018
How Many Samples are Needed to Estimate a Convolutional Neural Network? NIPS 2018
Clustering Semi-Random Mixtures of Gaussians ICML 2018
Scalable Hash-Based Estimation of Divergence Measures AISTATS 2018
TensorCast: Forecasting Time-Evolving Networks with Contextual Information IJCAI 2018
Rates of Convergence of Spectral Methods for Graphon Estimation ICML 2018
Exact and Robust Conformal Inference Methods for Predictive Machine Learning with Dependent Data COLT 2018