530 search results - page 39 / 106 » Learning Bounds for Domain Adaptation |
92
Voted
IJCAI
1989
15 years 1 months ago
1989
Learning how to make decisions in a domain is a critical aspect of intelligent planning behavior. The ability of a planner to adapt its decision-making to a domain depends in part...
85
Voted
GECCO
2005
Springer
15 years 6 months ago
2005
Springer
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
111
Voted
ECML
1991
Springer
15 years 4 months ago
1991
Springer
Robust reasoning requires learning from problem solving episodes. Past experience must be compiled to provide adaptation to new contingencies and intelligent modification of solut...
118
Voted
ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
134
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ICALP
2011
Springer
14 years 4 months ago
2011
Springer
We study the problem of navigating through a database of similar objects using comparisons. This problem is known to be strongly related to the small-world network design problem....