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NIPS
2004
15 years 5 months ago
Schema Learning: Experience-Based Construction of Predictive Action Models
Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
Michael P. Holmes, Charles Lee Isbell Jr.
UAI
2003
15 years 5 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
ICML
2010
IEEE
15 years 5 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
121
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DSS
2007
120views more  DSS 2007»
15 years 4 months ago
Could the use of a knowledge-based system lead to implicit learning?
The primary objective of a knowledge-based system (KBS) is to use stored knowledge to provide support for decision-making activities. Empirical studies identify improvements in de...
Solomon R. Antony, Radhika Santhanam
IJRR
2010
93views more  IJRR 2010»
15 years 3 months ago
Autonomous Helicopter Aerobatics through Apprenticeship Learning
Autonomous helicopter flight is widely regarded to be a highly challenging control problem. Despite this fact, human experts can reliably fly helicopters through a wide range of m...
Pieter Abbeel, Adam Coates, Andrew Y. Ng