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← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Statistical Learning
4,076 papers
Papers per year
2001: 2
2002: 8
2003: 9
2004: 7
2005: 9
2006: 34
2007: 37
2008: 34
2009: 41
2010: 62
2011: 68
2012: 81
2013: 109
2014: 120
2015: 99
2016: 149
2017: 160
2018: 205
2019: 285
2020: 376
2021: 433
2022: 447
2023: 577
2024: 488
2025: 192
2026: 44
Papers
Automatic identification of writers’ intentions: Comparing different methods for predicting relationship goals in online dating profile texts
EMNLP 2019
Semantic Alignment: Finding Semantically Consistent Ground-Truth for Facial Landmark Detection
CVPR 2019
Partitioning Structure Learning for Segmented Linear Regression Trees
NIPS 2019
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits
ICML 2019
Precision Matrix Estimation with Noisy and Missing Data
AISTATS 2019
Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly
COLT 2019
Distributionally Robust Optimization and Generalization in Kernel Methods
NIPS 2019
An Exponential Tail Bound for the Deleted Estimate
AAAI 2019
Stochastic Constraint Propagation for Mining Probabilistic Networks
IJCAI 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows
AISTATS 2019
Multiway clustering via tensor block models
NIPS 2019
Functional Isolation Forest
ACML 2019
Sample Complexity of Sinkhorn Divergences
AISTATS 2019
Rates of Convergence for Large-scale Nearest Neighbor Classification
NIPS 2019
Nonuniformity of P-values Can Occur Early in Diverging Dimensions
JMLR 2019
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
NIPS 2019
More Efficient Off-Policy Evaluation through Regularized Targeted Learning
ICML 2019
When can unlabeled data improve the learning rate?
COLT 2019
Robust Estimation of Tree Structured Gaussian Graphical Models
ICML 2019
Bounding Uncertainty for Active Batch Selection
AAAI 2019
PAC-Bayes Un-Expected Bernstein Inequality
NIPS 2019
Towards Clustering High-dimensional Gaussian Mixture Clouds in Linear Running Time
AISTATS 2019
Evaluating Research Novelty Detection: Counterfactual Approaches
EMNLP 2019
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
ICML 2019
First order expansion of convex regularized estimators
NIPS 2019
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