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» Learning Stochastic Logic Programs
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POPL
2007
ACM
14 years 8 months ago
Program verification as probabilistic inference
In this paper, we propose a new algorithm for proving the validity or invalidity of a pre/postcondition pair for a program. The algorithm is motivated by the success of the algori...
Sumit Gulwani, Nebojsa Jojic
CISS
2007
IEEE
13 years 11 months ago
Channel-Adaptive Optimal OFDMA Scheduling
Abstract-Joint subcarrier, power and rate allocation in orthogonal frequency division multiple access (OFDMA) scheduling is investigated for both downlink and uplink wireless trans...
Xin Wang, Georgios B. Giannakis, Yingqun Yu
ICML
2004
IEEE
14 years 8 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
ATAL
2007
Springer
14 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
ML
1998
ACM
101views Machine Learning» more  ML 1998»
13 years 7 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto