Papers
4,122 papers found
Should We Really Use Post-Hoc Tests Based on Mean-Ranks?
Alessio Benavoli, Giorgio Corani, Francesca Mangili
Sparse PCA via Covariance Thresholding
Yash Deshpande, Andrea Montanari
Sparsity and Error Analysis of Empirical Feature-Based Regularization Schemes
Xin Guo, Jun Fan, Ding-Xuan Zhou
Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing
Yuchen Zhang, Xi Chen, Dengyong Zhou et al.
Spectral Ranking using Seriation
Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic
SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions
Shusen Wang, Luo Luo, Zhihua Zhang
Stability and Generalization in Structured Prediction
Ben London, Bert Huang, Lise Getoor
Stable Graphical Models
Navodit Misra, Ercan E. Kuruoglu
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
Jure Žbontar, Yann LeCun
String and Membrane Gaussian Processes
Yves-Laurent Kom Samo, Stephen J. Roberts
StructED: Risk Minimization in Structured Prediction
Yossi Adi, Joseph Keshet
Structure Discovery in Bayesian Networks by Sampling Partial Orders
Teppo Niinimäki, Pekka Parviainen, Mikko Koivisto
Structure Learning in Bayesian Networks of a Moderate Size by Efficient Sampling
Ru He, Jin Tian, Huaiqing Wu
Structure-Leveraged Methods in Breast Cancer Risk Prediction
Jun Fan, Yirong Wu, Ming Yuan et al.
Subspace Learning with Partial Information
Alon Gonen, Dan Rosenbaum, Yonina C. Eldar et al.
Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes
Yuanjia Wang, Tianle Chen, Donglin Zeng
Synergy of Monotonic Rules
Vladimir Vapnik, Rauf Izmailov
The Asymptotic Performance of Linear Echo State Neural Networks
Romain Couillet, Gilles Wainrib, Harry Sevi et al.
The Benefit of Multitask Representation Learning
Andreas Maurer, Massimiliano Pontil, Bernardino Romera-Paredes
The Constrained Dantzig Selector with Enhanced Consistency
Yinfei Kong, Zemin Zheng, Jinchi Lv
The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes
Ramin Moghaddass, Cynthia Rudin, David Madigan
The LRP Toolbox for Artificial Neural Networks
Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon et al.
The Optimal Sample Complexity of PAC Learning
Steve Hanneke
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs
Alberto N. Escalante-B., Laurenz Wiskott