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» Maximal Intersection Queries in Randomized Input Models
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PKDD
2007
Springer
91views Data Mining» more  PKDD 2007»
15 years 6 months ago
Domain Adaptation of Conditional Probability Models Via Feature Subsetting
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
Sandeepkumar Satpal, Sunita Sarawagi
92
Voted
SODA
2010
ACM
181views Algorithms» more  SODA 2010»
15 years 9 months ago
On the Cell Probe Complexity of Dynamic Membership
We study the dynamic membership problem, one of the most fundamental data structure problems, in the cell probe model with an arbitrary cell size. We consider a cell probe model e...
KE YI, QIN ZHANG
AAAI
2008
15 years 2 months ago
Lifted Probabilistic Inference with Counting Formulas
Lifted inference algorithms exploit repeated structure in probabilistic models to answer queries efficiently. Previous work such as de Salvo Braz et al.'s first-order variabl...
Brian Milch, Luke S. Zettlemoyer, Kristian Kerstin...
102
Voted
ICCV
2007
IEEE
16 years 2 months ago
Objects in Context
In the task of visual object categorization, semantic context can play the very important role of reducing ambiguity in objects' visual appearance. In this work we propose to...
Andrew Rabinovich, Andrea Vedaldi, Carolina Galleg...
CORR
2010
Springer
94views Education» more  CORR 2010»
14 years 11 months ago
When LP is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings
Abstract Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy match...
Nikhil Bansal, Anupam Gupta, Jian Li, Juliá...