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NIPS
2004
14 years 8 days ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
AAAI
2000
14 years 7 days ago
Iterative Flattening: A Scalable Method for Solving Multi-Capacity Scheduling Problems
One challenge for research in constraint-based scheduling has been to produce scalable solution procedures under fairly general representational assumptions. Quite often, the comp...
Amedeo Cesta, Angelo Oddi, Stephen F. Smith
SGP
2003
14 years 7 days ago
Provably Good Surface Sampling and Approximation
We present an algorithm for meshing surfaces that is a simple adaptation of a greedy “farthest point” technique proposed by Chew. Given a surface S, it progressively adds poin...
Steve Oudot, Jean-Daniel Boissonnat
KYOTODL
2000
122views more  KYOTODL 2000»
14 years 7 days ago
Federation Services for Heterogeneous Digital Libraries Accessing Cooperative and Non-Cooperative Sources
Today, bibliographical information is kept in a variety of digital libraries available on the Internet. The integration of bibliographical data is considered as one of the most im...
Martin Endig, Michael Höding, Gunter Saake, K...
ATAL
2010
Springer
14 years 7 hour ago
Planning against fictitious players in repeated normal form games
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Enrique Munoz de Cote, Nicholas R. Jennings