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» Guarantees for Approximate Incremental SVMs
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AAAI
2010
14 years 11 months ago
Efficient Belief Propagation for Utility Maximization and Repeated Inference
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
Aniruddh Nath, Pedro Domingos
NIPS
1998
14 years 11 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
CGF
2005
159views more  CGF 2005»
14 years 9 months ago
Real-Time Shape Editing using Radial Basis Functions
Current surface-based methods for interactive freeform editing of high resolution 3D models are very powerful, but at the same time require a certain minimum tessellation or sampl...
Mario Botsch, Leif Kobbelt
ICML
1999
IEEE
15 years 10 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
VLDB
2001
ACM
114views Database» more  VLDB 2001»
15 years 2 months ago
Distinct Sampling for Highly-Accurate Answers to Distinct Values Queries and Event Reports
Estimating the number of distinct values is a wellstudied problem, due to its frequent occurrence in queries and its importance in selecting good query plans. Previous work has sh...
Phillip B. Gibbons