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IJCV
2010
152views more  IJCV 2010»
15 years 3 months ago
Learning Articulated Structure and Motion
Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to learn the st...
David A. Ross, Daniel Tarlow, Richard S. Zemel
153
Voted
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 3 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
192
Voted
ICASSP
2011
IEEE
14 years 8 months ago
Improving kernel-energy trade-offs for machine learning in implantable and wearable biomedical applications
Emerging biomedical sensors and stimulators offer unprecedented modalities for delivering therapy and acquiring physiological signals (e.g., deep brain stimulators). Exploiting th...
Kyong-Ho Lee, Sun-Yuan Kung, Naveen Verma
SIGCOMM
2012
ACM
13 years 7 months ago
SP4: scalable programmable packet processing platform
We propose the demonstration of SP4, a software-based programmable packet processing platform that supports (1) stateful packet processing useful for analyzing traffic flows wit...
Harjot Gill, Dong Lin, Lohit Sarna, Robert Mead, K...
ICML
1999
IEEE
15 years 9 months ago
Learning Hierarchical Performance Knowledge by Observation
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Michael van Lent, John E. Laird