Papers
3,706 papers found
Matrix Completion from Power-Law Distributed Samples
Raghu Meka, Prateek Jain, Inderjit S. Dhillon
Information-theoretic lower bounds on the oracle complexity of convex optimization
Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett et al.
Nonlinear Learning using Local Coordinate Coding
Kai Yu, Tong Zhang, Yihong Gong
Compositionality of optimal control laws
Emanuel Todorov
Learning with Compressible Priors
Volkan Cevher
Matrix Completion from Noisy Entries
Raghunandan Keshavan, Andrea Montanari, Sewoong Oh
Human Rademacher Complexity
Xiaojin Zhu, Bryan R. Gibson, Timothy T. Rogers
Beyond Convexity: Online Submodular Minimization
Elad Hazan, Satyen Kale
Measuring model complexity with the prior predictive
Wolf Vanpaemel
Complexity of Decentralized Control: Special Cases
Martin Allen, Shlomo Zilberstein
Permutation Complexity Bound on Out-Sample Error
Malik Magdon-Ismail
Linear Complementarity for Regularized Policy Evaluation and Improvement
Jeffrey Johns, Christopher Painter-wakefield, Ronald Parr
Sample Complexity of Testing the Manifold Hypothesis
Hariharan Narayanan, Sanjoy Mitter
Tight Sample Complexity of Large-Margin Learning
Sivan Sabato, Nathan Srebro, Naftali Tishby
On the Convexity of Latent Social Network Inference
Seth Myers, Jure Leskovec
Online Learning: Random Averages, Combinatorial Parameters, and Learnability
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers
Luca Oneto, Davide Anguita, Alessandro Ghio et al.
ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning
Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam et al.
Composite Multiclass Losses
Elodie Vernet, Mark D. Reid, Robert C. Williamson
Complexity of Inference in Latent Dirichlet Allocation
David Sontag, Dan Roy
A Denoising View of Matrix Completion
Weiran Wang, Miguel Á. Carreira-Perpiñán, Zhengdong Lu
Matrix Completion for Multi-label Image Classification
Ricardo S. Cabral, Fernando Torre, Joao P. Costeira et al.
Learning to Learn with Compound HD Models
Antonio Torralba, Joshua B. Tenenbaum, Ruslan Salakhutdinov
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning
Marius Kloft, Gilles Blanchard