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» Testing Incremental Adaptation
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IUI
2000
ACM
14 years 7 days ago
Learning to recommend from positive evidence
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that nee...
Ingo Schwab, Wolfgang Pohl, Ivan Koychev
AGENTS
1999
Springer
14 years 5 days ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
IPPS
1999
IEEE
14 years 5 days ago
Non-Preemptive Scheduling of Real-Time Threads on Multi-Level-Context Architectures
The rapid progress in high-performance microprocessor design has made it di cult to adapt real-time scheduling results to new models of microprocessor hardware, thus leaving an un...
Jan Jonsson, Henrik Lönn, Kang G. Shin
SIGGRAPH
1998
ACM
14 years 3 days ago
Progressive Forest Split Compression
In this paper we introduce the Progressive Forest Split (PFS) representation, a new adaptive refinement scheme for storing and transmitting manifold triangular meshes in progress...
Gabriel Taubin, André Guéziec, Willi...
SIGGRAPH
1992
ACM
13 years 12 months ago
Interactive inspection of solids: cross-sections and interferences
To reduce the cost of correcting design errors, assemblies of mechanical parts are modeled using CAD systems and verified electronically before the designs are sent to manufacturi...
Jarek Rossignac, Abe Megahed, Bengt-Olaf Schneider