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» The Localization Hypothesis and Machines
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151
Voted
ML
2002
ACM
178views Machine Learning» more  ML 2002»
15 years 11 days ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
126
Voted
ICMLA
2010
14 years 10 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
ALT
2011
Springer
14 years 21 days ago
On Noise-Tolerant Learning of Sparse Parities and Related Problems
We consider the problem of learning sparse parities in the presence of noise. For learning parities on r out of n variables, we give an algorithm that runs in time poly log 1 δ , ...
Elena Grigorescu, Lev Reyzin, Santosh Vempala
EUROPAR
2006
Springer
15 years 4 months ago
A Hierarchical CLH Queue Lock
Abstract. Modern multiprocessor architectures such as CC-NUMA machines or CMPs have nonuniform communication architectures that render programs sensitive to memory access locality....
Victor Luchangco, Daniel Nussbaum, Nir Shavit
LCPC
2007
Springer
15 years 6 months ago
Multidimensional Blocking in UPC
Abstract. Partitioned Global Address Space (PGAS) languages offer an attractive, high-productivity programming model for programming large-scale parallel machines. PGAS languages, ...
Christopher Barton, Calin Cascaval, George Alm&aac...