Papers
4,122 papers found
On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm
Ery Arias-Castro, David Mason, Bruno Pelletier
On the Influence of Momentum Acceleration on Online Learning
Kun Yuan, Bicheng Ying, Ali H. Sayed
On the properties of variational approximations of Gibbs posteriors
Pierre Alquier, James Ridgway, Nicolas Chopin
Operator-valued Kernels for Learning from Functional Response Data
Hachem Kadri, Emmanuel Duflos, Philippe Preux et al.
Optimal Estimation and Completion of Matrices with Biclustering Structures
Chao Gao, Yu Lu, Zongming Ma et al.
Optimal Estimation of Derivatives in Nonparametric Regression
Wenlin Dai, Tiejun Tong, Marc G. Genton
Optimal Learning Rates for Localized SVMs
Mona Meister, Ingo Steinwart
Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach
Jenna Wiens, John Guttag, Eric Horvitz
Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models
Jiahe Lin, Sumanta Basu, Moulinath Banerjee et al.
Practical Kernel-Based Reinforcement Learning
André M.S. Barreto, Doina Precup, Joelle Pineau
Probabilistic Low-Rank Matrix Completion from Quantized Measurements
Sonia A. Bhaskar
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
James Townsend, Niklas Koep, Sebastian Weichwald
Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests
Lucas Mentch, Giles Hooker
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Haim Avron, Vikas Sindhwani, Jiyan Yang et al.
Random Rotation Ensembles
Rico Blaser, Piotr Fryzlewicz
Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices
Dan Yang, Zongming Ma, Andreas Buja
Refined Error Bounds for Several Learning Algorithms
Steve Hanneke
Regularized Policy Iteration with Nonparametric Function Spaces
Amir-massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári et al.
Revisiting the Nyström Method for Improved Large-scale Machine Learning
Alex Gittens, Michael W. Mahoney
RLScore: Regularized Least-Squares Learners
Tapio Pahikkala, Antti Airola
Rounding-based Moves for Semi-Metric Labeling
M. Pawan Kumar, Puneet K. Dokania
Scalable Learning of Bayesian Network Classifiers
Ana M. Martínez, Geoffrey I. Webb, Shenglei Chen et al.
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics
Stephan Clémençon, Igor Colin, Aurélien Bellet
Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues
David Rohde, Matt P. Wand