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» Learning and Domain Adaptation
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ICML
2004
IEEE
16 years 7 months ago
Communication complexity as a lower bound for learning in games
A fast-growing body of research in the AI and machine learning communities addresses learning in games, where there are multiple learners with different interests. This research a...
Vincent Conitzer, Tuomas Sandholm
ICML
2003
IEEE
16 years 7 months ago
On Kernel Methods for Relational Learning
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Chad M. Cumby, Dan Roth
ICML
2001
IEEE
16 years 7 months ago
Convergence of Gradient Dynamics with a Variable Learning Rate
As multiagent environments become more prevalent we need to understand how this changes the agent-based paradigm. One aspect that is heavily affected by the presence of multiple a...
Michael H. Bowling, Manuela M. Veloso
AAAI
2008
15 years 9 months ago
A Case Study on the Critical Role of Geometric Regularity in Machine Learning
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Jason Gauci, Kenneth O. Stanley
ICSE
2008
IEEE-ACM
16 years 7 months ago
Time-bounded adaptation for automotive system software
Software is increasingly deployed in vehicles as demand for new functionality increases and cheaper and more powerful hardware becomes available. Likewise, emerging wireless commu...
Aline Senart, Douglas C. Schmidt, Serena Fritsch, ...