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ICML
2010
IEEE
15 years 3 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
ICAC
2006
IEEE
15 years 9 months ago
A Runtime Adaptation Framework for Native C and Bytecode Applications
— The need for self-healing software to respond with a reactive, proactive or preventative action as a result of changes in its environment has added the non-functional requireme...
Rean Griffith, Gail E. Kaiser
119
Voted
COLING
2008
15 years 4 months ago
Investigating Statistical Techniques for Sentence-Level Event Classification
The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Summarisation. In ...
Martina Naughton, Nicola Stokes, Joe Carthy
VEE
2012
ACM
238views Virtualization» more  VEE 2012»
13 years 10 months ago
Swift: a register-based JIT compiler for embedded JVMs
Code quality and compilation speed are two challenges to JIT compilers, while selective compilation is commonly used to tradeoff these two issues. Meanwhile, with more and more Ja...
Yuan Zhang, Min Yang, Bo Zhou, Zhemin Yang, Weihua...
ICML
2009
IEEE
16 years 3 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...