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» An Instance Selection Approach to Multiple Instance Learning
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MICRO
2002
IEEE
164views Hardware» more  MICRO 2002»
15 years 2 months ago
A quantitative framework for automated pre-execution thread selection
Pre-execution attacks cache misses for which conventional address-prediction driven prefetching is ineffective. In pre-execution, copies of cache miss computations are isolated fr...
Amir Roth, Gurindar S. Sohi
ECCV
2008
Springer
15 years 11 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
BTW
2009
Springer
99views Database» more  BTW 2009»
15 years 1 months ago
A Framework for Reasoning about Share Equivalence and Its Integration into a Plan Generator
: Very recently, Cao et al. presented the MAPLE approach, which accelerates queries with multiple instances of the same relation by sharing their scan operator. The principal idea ...
Thomas Neumann, Guido Moerkotte
INFOCOM
2012
IEEE
13 years 9 days ago
Di-Sec: A distributed security framework for heterogeneous Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are no longer a nascent technology and today, they are actively deployed as a viable technology in many diverse application domains such as health ...
Marco Valero, Sang Shin Jung, A. Selcuk Uluagac, Y...
JMLR
2011
192views more  JMLR 2011»
14 years 4 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...