Papers
176,624 papers found
Ellipsoidal Support Vector Machines
Michinari Momma, Kohei Hatano, Hiroki Nakayama
Elliptical slice sampling
Iain Murray, Ryan Adams, David MacKay
Empirical Bernstein Boosting
Pannagadatta Shivaswamy, Tony Jebara
Empirical Bernstein Inequalities for U-Statistics
Thomas Peel, Sandrine Anthoine, Liva Ralaivola
Empirical Risk Minimization with Approximations of Probabilistic Grammars
Noah A. Smith, Shay B. Cohen
Energy Disaggregation via Discriminative Sparse Coding
J. Z. Kolter, Siddharth Batra, Andrew Y. Ng
Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures
Kamiya Motwani, Nagesh Adluru, Chris Hinrichs et al.
Erratum: SGDQN is Less Careful than Expected
Antoine Bordes, Léon Bottou, Patrick Gallinari et al.
Error-Correcting Output Codes Library
Sergio Escalera, Oriol Pujol, Petia Radeva
Error Propagation for Approximate Policy and Value Iteration
Amir-massoud Farahmand, Csaba Szepesvári, Rémi Munos
Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces
Abhinav Gupta, Martial Hebert, Takeo Kanade et al.
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
Aapo Hyvärinen, Kun Zhang, Shohei Shimizu et al.
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
Dávid Pál, Barnabás Póczos, Csaba Szepesvári
Evaluating neuronal codes for inference using Fisher information
Haefner Ralf, Matthias Bethge
Evaluation of Rarity of Fingerprints in Forensics
Chang Su, Sargur Srihari
Evidence-Specific Structures for Rich Tractable CRFs
Anton Chechetka, Carlos Guestrin
Evolving Static Representations for Task Transfer
Phillip Verbancsics, Kenneth O. Stanley
Exact inference and learning for cumulative distribution functions on loopy graphs
Nebojsa Jojic, Chris Meek, Jim C. Huang
Exact learning curves for Gaussian process regression on large random graphs
Matthew Urry, Peter Sollich
Exclusive Lasso for Multi-task Feature Selection
Yang Zhou, Rong Jin, Steven Chu–Hong Hoi
Expectation Truncation and the Benefits of Preselection In Training Generative Models
Jörg Lücke, Julian Eggert
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net
Alexander Lorbert, David Eis, Victoria Kostina et al.
Exploiting Feature Covariance in High-Dimensional Online Learning
Justin Ma, Alex Kulesza, Mark Dredze et al.
Exploiting the High Predictive Power of Multi-class Subgroups
Tarek Abudawood, Peter Flach
Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach
Alessandro Bergamo, Lorenzo Torresani