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MOBISYS
2010
ACM
15 years 13 days ago
Darwin phones: the evolution of sensing and inference on mobile phones
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on ...
Emiliano Miluzzo, Cory Cornelius, Ashwin Ramaswamy...
ATAL
2008
Springer
15 years 3 days ago
On the usefulness of opponent modeling: the Kuhn Poker case study
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
NIPS
1993
14 years 11 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
CG
2007
Springer
14 years 10 months ago
An evaluation of user experience with a sketch-based 3D modeling system
With the availability of pen-enabled digital hardware, sketch-based 3D modeling is becoming an increasingly attractive alternative to traditional methods in many design environmen...
Levent Burak Kara, Kenji Shimada, Sarah D. Marmale...
AIR
2004
113views more  AIR 2004»
14 years 10 months ago
Class Noise vs. Attribute Noise: A Quantitative Study
Real-world data is never perfect and can often suffer from corruptions (noise) that may impact interpretations of the data, models created from the data and decisions made based on...
Xingquan Zhu, Xindong Wu