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ICML
2004
IEEE
16 years 19 days ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
ESANN
2006
15 years 1 months ago
An algorithm for fast and reliable ESOM learning
The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
Mario Nöcker, Fabian Mörchen, Alfred Ult...
ICALP
1998
Springer
15 years 3 months ago
A Neuroidal Architecture for Cognitive Computation
An architecture is described for designing systems that acquire and manipulate large amounts of unsystematized, or so-called commonsense, knowledge. Its aim is to exploit to the fu...
Leslie G. Valiant
ICML
2006
IEEE
16 years 19 days ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
ICML
2005
IEEE
16 years 19 days ago
Exploration and apprenticeship learning in reinforcement learning
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Pieter Abbeel, Andrew Y. Ng