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AGI
2011
14 years 10 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia
AAAI
2010
15 years 8 months ago
Structure Learning for Markov Logic Networks with Many Descriptive Attributes
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyua...
CEC
2003
IEEE
15 years 12 months ago
Learning DFA: evolution versus evidence driven state merging
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
Simon M. Lucas, T. Jeff Reynolds
CIDM
2007
IEEE
15 years 10 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
AAAI
2008
15 years 9 months ago
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...