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STOC
2005
ACM
129views Algorithms» more  STOC 2005»
16 years 7 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
ISCA
2006
IEEE
138views Hardware» more  ISCA 2006»
16 years 19 days ago
Learning-Based SMT Processor Resource Distribution via Hill-Climbing
The key to high performance in Simultaneous Multithreaded (SMT) processors lies in optimizing the distribution of shared resources to active threads. Existing resource distributio...
Seungryul Choi, Donald Yeung
SBIA
2004
Springer
15 years 12 months ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
NIPS
1996
15 years 8 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies
ECCV
2010
Springer
15 years 6 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof