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» Reformulating Constraint Models Using Input Data
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NIPS
2003
15 years 4 months ago
Nonstationary Covariance Functions for Gaussian Process Regression
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
Christopher J. Paciorek, Mark J. Schervish
TOH
2008
98views more  TOH 2008»
15 years 3 months ago
Six-DoF Haptic Rendering of Contact Between Geometrically Complex Reduced Deformable Models
Real-time evaluation of distributed contact forces between rigid or deformable 3D objects is a key ingredient of 6-DoF force-feedback rendering. Unfortunately, at very high tempora...
Jernej Barbic, Doug L. James
JSW
2007
116views more  JSW 2007»
15 years 3 months ago
Security Patterns for Voice over IP Networks
—Voice over IP (VoIP) has had a strong effect on global communications by allowing human voice and fax information to travel over existing packet data networks along with traditi...
Eduardo B. Fernández, Juan C. Pelaez, Mar&i...
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
15 years 4 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro
JMLR
2010
134views more  JMLR 2010»
14 years 10 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...