Papers
4,122 papers found
Robust Online Gesture Recognition with Crowdsourced Annotations
Long-Van Nguyen-Dinh, Alberto Calatroni, Gerhard Tröster
Seeded Graph Matching for Correlated Erdos-Renyi Graphs
Vince Lyzinski, Donniell E. Fishkind, Carey E. Priebe
Semi-Supervised Eigenvectors for Large-Scale Locally-Biased Learning
Toke J. Hansen, Michael W. Mahoney
Set-Valued Approachability and Online Learning with Partial Monitoring
Shie Mannor, Vianney Perchet, Gilles Stoltz
Sparse Factor Analysis for Learning and Content Analytics
Andrew S. Lan, Andrew E. Waters, Christoph Studer et al.
Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity
Shay B. Cohen, Karl Stratos, Michael Collins et al.
SPMF: A Java Open-Source Pattern Mining Library
Philippe Fournier-Viger, Antonio Gomariz, Ted Gueniche et al.
Statistical Analysis of Metric Graph Reconstruction
Fabrizio Lecci, Alessandro Rinaldo, Larry Wasserman
Structured Prediction via Output Space Search
Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli
Tensor Decompositions for Learning Latent Variable Models
Animashree Anandkumar, Rong Ge, Daniel Hsu et al.
The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R
Haotian Pang, Han Liu, Robert Vanderbei
The Gesture Recognition Toolkit
Nicholas Gillian, Joseph A. Paradiso
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
Matthew D. Hoffman, Andrew Gelman
The Student-t Mixture as a Natural Image Patch Prior with Application to Image Compression
Aäron van den Oord, Benjamin Schrauwen
Towards Ultrahigh Dimensional Feature Selection for Big Data
Mingkui Tan, Ivor W. Tsang, Li Wang
Training Highly Multiclass Classifiers
Maya R. Gupta, Samy Bengio, Jason Weston
Transfer Learning Decision Forests for Gesture Recognition
Norberto A. Goussies, Sebastián Ubalde, Marta Mejail
Unbiased Generative Semi-Supervised Learning
Patrick Fox-Roberts, Edward Rosten
Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning
Aaron Wilson, Alan Fern, Prasad Tadepalli
What Regularized Auto-Encoders Learn from the Data-Generating Distribution
Guillaume Alain, Yoshua Bengio
A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics
Hervé Frezza-Buet, Matthieu Geist
A Framework for Evaluating Approximation Methods for Gaussian Process Regression
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray
Algorithms and Hardness Results for Parallel Large Margin Learning
Philip M. Long, Rocco A. Servedio