Papers
176,624 papers found
Neurometric function analysis of population codes
Philipp Berens, Sebastian Gerwinn, Alexander Ecker et al.
NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM
Pradip Ghanty, Samrat Paul, Nikhil R. Pal
Nieme: Large-Scale Energy-Based Models
Francis Maes
No evidence for active sparsification in the visual cortex
Pietro Berkes, Ben White, Jozsef Fiser
Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording
Zhi Yang, Qi Zhao, Edward Keefer et al.
Noisy Generalized Binary Search
Robert Nowak
Nonextensive Information Theoretic Kernels on Measures
André F. T. Martins, Noah A. Smith, Eric P. Xing et al.
Nonlinear directed acyclic structure learning with weakly additive noise models
Arthur Gretton, Peter Spirtes, Robert E. Tillman
Nonlinear Learning using Local Coordinate Coding
Kai Yu, Tong Zhang, Yihong Gong
Nonlinear Models Using Dirichlet Process Mixtures
Babak Shahbaba, Radford Neal
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations
Mingyuan Zhou, Haojun Chen, Lu Ren et al.
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution
Cosmin Bejan, Matthew Titsworth, Andrew Hickl et al.
Nonparametric Bayesian Texture Learning and Synthesis
Long Zhu, Yuanahao Chen, Bill Freeman et al.
Nonparametric Greedy Algorithms for the Sparse Learning Problem
Han Liu, Xi Chen
Nonparametric Latent Feature Models for Link Prediction
Kurt Miller, Michael I. Jordan, Thomas L. Griffiths
Non-parametric learning to aid path planning over slopes
S. Karumanchi, T. Allen, T. Bailey and S. Scheding
Non-stationary continuous dynamic Bayesian networks
Marco Grzegorczyk, Dirk Husmeier
Occlusive Components Analysis
Jörg Lücke, Richard Turner, Maneesh Sahani et al.
On Efficient Large Margin Semisupervised Learning: Method and Theory
Junhui Wang, Xiaotong Shen, Wei Pan
On Invariance in Hierarchical Models
Jake Bouvrie, Lorenzo Rosasco, Tomaso Poggio
On Learning Rotations
Raman Arora
Online Learning of Assignments
Matthew Streeter, Daniel Golovin, Andreas Krause
Online Learning with Sample Path Constraints
Shie Mannor, John N. Tsitsiklis, Jia Yuan Yu
Online Learning with Samples Drawn from Non-identical Distributions
Ting Hu, Ding-Xuan Zhou
On Stochastic and Worst-case Models for Investing
Elad Hazan, Satyen Kale