Papers
184,605 papers found
Compositionality of optimal control laws
Emanuel Todorov
Compressed Least-Squares Regression
Odalric Maillard, Rémi Munos
Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors
Mathias Drton, Michael Eichler, Thomas S. Richardson
Conditional Neural Fields
Jian Peng, Liefeng Bo, Jinbo Xu
Conditional Random Fields with High-Order Features for Sequence Labeling
Nan Ye, Wee S. Lee, Hai L. Chieu et al.
Consistency and Localizability
Alon Zakai, Ya'acov Ritov
Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection
Roy Anati, Kostas Daniilidis
Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation
Hamid R. Maei, Csaba Szepesvári, Shalabh Bhatnagar et al.
Convex Relaxation of Mixture Regression with Efficient Algorithms
Novi Quadrianto, John Lim, Dale Schuurmans et al.
Cooperative manipulation and transportation with aerial robots
N. Michael, J. Fink and V. Kumar
Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies
Arno Onken, Steffen Grünewälder, Klaus Obermayer
Data-driven calibration of linear estimators with minimal penalties
Sylvain Arlot, Francis R. Bach
Data-driven Calibration of Penalties for Least-Squares Regression
Sylvain Arlot, Pascal Massart
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
Chong Wang, David M. Blei
Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods
Christian Rieger, Barbara Zwicknagl
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning
Anne Hsu, Thomas L. Griffiths
Directed Regression
Yi-hao Kao, Benjamin V. Roy, Xiang Yan
Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora
Shuang-hong Yang, Hongyuan Zha, Bao-gang Hu
Discrete MDL Predicts in Total Variation
Marcus Hutter
Discriminative Learning Under Covariate Shift
Steffen Bickel, Michael Brückner, Tobias Scheffer
Discriminative Network Models of Schizophrenia
Irina Rish, Benjamin Thyreau, Bertrand Thirion et al.
Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger, Lawrence K. Saul
Distributed Algorithms for Topic Models
David Newman, Arthur Asuncion, Padhraic Smyth et al.