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IJCAI
2007
15 years 8 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
LREC
2008
170views Education» more  LREC 2008»
15 years 8 months ago
A Semantic Memory for Incremental Ontology Population
Generally, ontology learning and population is applied as a semi-automatic approach to knowledge acquisition in natural language understanding systems. That means, after the ontol...
Berenike Loos, Lasse Schwarten
IMECS
2007
15 years 8 months ago
A Hybrid Markov Model for Accurate Memory Reference Generation
—Workload characterisation and generation is becoming an increasingly important area as hardware and application complexities continue to advance. In this paper, we introduce a c...
Rahman Hassan, Antony Harris
NIPS
2007
15 years 8 months ago
Variational Inference for Diffusion Processes
Diffusion processes are a family of continuous-time continuous-state stochastic processes that are in general only partially observed. The joint estimation of the forcing paramete...
Cédric Archambeau, Manfred Opper, Yuan Shen...
WCET
2008
15 years 8 months ago
Traces as a Solution to Pessimism and Modeling Costs in WCET Analysis
WCET analysis models for superscalar out-of-order CPUs generally need to be pessimistic in order to account for a wide range of possible dynamic behavior. CPU hardware modificatio...
Jack Whitham, Neil C. Audsley