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CORR
2010
Springer
207views Education» more  CORR 2010»
15 years 6 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
SIGIR
2004
ACM
16 years 4 days ago
Corpus structure, language models, and ad hoc information retrieval
Most previous work on the recently developed languagemodeling approach to information retrieval focuses on document-specific characteristics, and therefore does not take into acc...
Oren Kurland, Lillian Lee
MIS
2007
Springer
159views Multimedia» more  MIS 2007»
15 years 6 months ago
The application of fluid mobility modelling in wireless cellular networks
Mobility models, synthetic or trace, try to accurately model the movement of a single user or a group of users. Models are used in simulators and emulators to investigate the cons...
Ronan J. Skehill, Sean McGrath
IROS
2009
IEEE
152views Robotics» more  IROS 2009»
16 years 1 months ago
EMG-to-force estimation with full-scale physiology based muscle model
— EMG-to-force estimation for voluntary muscle contraction has many applications in human-machine interaction, motion analysis, and rehabilitation robotics for prosthetic limbs o...
Mitsuhiro Hayashibe, David Guiraud, Philippe Poign...
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
16 years 7 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...