Papers
4,122 papers found
Keep It Simple And Sparse: Real-Time Action Recognition
Sean Ryan Fanello, Ilaria Gori, Giorgio Metta et al.
Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels
Kenji Fukumizu, Le Song, Arthur Gretton
Language-Motivated Approaches to Action Recognition
Manavender R. Malgireddy, Ifeoma Nwogu, Venu Govindaraju
Large-scale SVD and Manifold Learning
Ameet Talwalkar, Sanjiv Kumar, Mehryar Mohri et al.
Learning Bilinear Model for Matching Queries and Documents
Wei Wu, Zhengdong Lu, Hang Li
Learning Theory Analysis for Association Rules and Sequential Event Prediction
Cynthia Rudin, Benjamin Letham, David Madigan
Lovasz theta function, SVMs and Finding Dense Subgraphs
Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya et al.
Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem
Antoine Salomon, Jean-Yves Audibert, Issam El Alaoui
Machine Learning with Operational Costs
Theja Tulabandhula, Cynthia Rudin
MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures With Low Probability of False Positives During Use
Daniel Kyu Hwa Kohlsdorf, Thad E. Starner
Maximum Volume Clustering: A New Discriminative Clustering Approach
Gang Niu, Bo Dai, Lin Shang et al.
Message-Passing Algorithms for Quadratic Minimization
Nicholas Ruozzi, Sekhar Tatikonda
MLPACK: A Scalable C++ Machine Learning Library
Ryan R. Curtin, James R. Cline, N. P. Slagle et al.
Multicategory Large-Margin Unified Machines
Chong Zhang, Yufeng Liu
Multi-Stage Multi-Task Feature Learning
Pinghua Gong, Jieping Ye, Changshui Zhang
Multivariate Convex Regression with Adaptive Partitioning
Lauren A. Hannah, David B. Dunson
Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
Jaakko Riihimäki, Pasi Jylänki, Aki Vehtari
Nonparametric Sparsity and Regularization
Lorenzo Rosasco, Silvia Villa, Sofia Mosci et al.
One-shot Learning Gesture Recognition from RGB-D Data Using Bag of Features
Jun Wan, Qiuqi Ruan, Wei Li et al.
On the Convergence of Maximum Variance Unfolding
Ery Arias-Castro, Bruno Pelletier
On the Learnability of Shuffle Ideals
Dana Angluin, James Aspnes, Sarah Eisenstat et al.
On the Mutual Nearest Neighbors Estimate in Regression
Arnaud Guyader, Nick Hengartner
Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality
Sébastien Bubeck, Damien Ernst, Aurélien Garivier