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» Generalizing over Several Learning Settings
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INFOCOM
1997
IEEE
13 years 12 months ago
VBR over VBR: The Homogeneous, Loss-Free Case
We consider the multiplexing of several variable bit rate (VBR) connections over one variable bit rate connection where the multiplexing uses a multiplexing bu er of size B. The V...
Silvia Giordano, Jean-Yves Le Boudec, Philippe Oec...
ML
1998
ACM
117views Machine Learning» more  ML 1998»
13 years 7 months ago
Learning Team Strategies: Soccer Case Studies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
NIPS
2007
13 years 9 months ago
Semi-Supervised Multitask Learning
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
Qiuhua Liu, Xuejun Liao, Lawrence Carin
IEICET
2007
114views more  IEICET 2007»
13 years 7 months ago
Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion
In order to obtain better learning results in supervised learning, it is important to choose model parameters appropriately. Model selection is usually carried out by preparing a ...
Shun Gokita, Masashi Sugiyama, Keisuke Sakurai
SIGMOD
2003
ACM
145views Database» more  SIGMOD 2003»
14 years 7 months ago
Evaluating Probabilistic Queries over Imprecise Data
Many applications employ sensors for monitoring entities such as temperature and wind speed. A centralized database tracks these entities to enable query processing. Due to contin...
Reynold Cheng, Dmitri V. Kalashnikov, Sunil Prabha...