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ICASSP
2011
IEEE
14 years 7 months ago
Improving kernel-energy trade-offs for machine learning in implantable and wearable biomedical applications
Emerging biomedical sensors and stimulators offer unprecedented modalities for delivering therapy and acquiring physiological signals (e.g., deep brain stimulators). Exploiting th...
Kyong-Ho Lee, Sun-Yuan Kung, Naveen Verma
LCTRTS
2007
Springer
15 years 10 months ago
Integrated CPU and l2 cache voltage scaling using machine learning
Embedded systems serve an emerging and diverse set of applications. As a result, more computational and storage capabilities are added to accommodate ever more demanding applicati...
Nevine AbouGhazaleh, Alexandre Ferreira, Cosmin Ru...
ACL
2009
15 years 1 months ago
Paraphrase Recognition Using Machine Learning to Combine Similarity Measures
This paper presents three methods that can be used to recognize paraphrases. They all employ string similarity measures apshallow abstractions of the input sentences, and a Maximu...
Prodromos Malakasiotis
ISPASS
2009
IEEE
15 years 10 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
CSL
2006
Springer
15 years 3 months ago
A study in machine learning from imbalanced data for sentence boundary detection in speech
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...