Papers
21,849 papers found
Multiscale Random Fields with Application to Contour Grouping
Longin J. Latecki, Chengen Lu, Marc Sobel et al.
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
Christopher Williams, Stefan Klanke, Sethu Vijayakumar et al.
Natural Image Denoising with Convolutional Networks
Viren Jain, Sebastian Seung
Near-minimax recursive density estimation on the binary hypercube
Maxim Raginsky, Svetlana Lazebnik, Rebecca Willett et al.
Near-optimal Regret Bounds for Reinforcement Learning
Peter Auer, Thomas Jaksch, Ronald Ortner
Nonlinear causal discovery with additive noise models
Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij et al.
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan et al.
Nonparametric regression and classification with joint sparsity constraints
Han Liu, Larry Wasserman, John D. Lafferty
Non-parametric Regression Between Manifolds
Florian Steinke, Matthias Hein
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images
Vincent Q. Vu, Bin Yu, Thomas Naselaris et al.
Nonrigid Structure from Motion in Trajectory Space
Ijaz Akhter, Yaser Sheikh, Sohaib Khan et al.
Non-stationary dynamic Bayesian networks
Joshua W. Robinson, Alexander J. Hartemink
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
Alex Graves, Jürgen Schmidhuber
On Bootstrapping the ROC Curve
Patrice Bertail, Stéphan J. Clémençcon, Nicolas Vayatis
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Benjamin Schrauwen, Lars Buesing, Robert A. Legenstein
One sketch for all: Theory and Application of Conditional Random Sampling
Ping Li, Kenneth W. Church, Trevor J. Hastie
Online Metric Learning and Fast Similarity Search
Prateek Jain, Brian Kulis, Inderjit S. Dhillon et al.
Online Models for Content Optimization
Deepak Agarwal, Bee-chung Chen, Pradheep Elango et al.
Online Optimization in X-Armed Bandits
Sébastien Bubeck, Gilles Stoltz, Csaba Szepesvári et al.
Online Prediction on Large Diameter Graphs
Mark Herbster, Guy Lever, Massimiliano Pontil
On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factor
Christoph Kolodziejski, Bernd Porr, Minija Tamosiunaite et al.
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost
Hamed Masnadi-shirazi, Nuno Vasconcelos
On the Efficient Minimization of Classification Calibrated Surrogates
Richard Nock, Frank Nielsen