Journal ArticleDOI
Pattern Recognition and Machine Learning
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TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
Citations
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Journal ArticleDOI
Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis
Franco J. Vizeacoumar,Nydia Van Dyk,Frederick S. Vizeacoumar,Vincent Cheung,Jingjing Li,Yaroslav Sydorskyy,Nicolle Case,Zhijian Li,Alessandro Datti,Corey Nislow,Brian Raught,Zhaolei Zhang,Brendan J. Frey,Kerry Bloom,Charles Boone,Brenda J. Andrews +15 more
TL;DR: A combination of yeast genetics, synthetic genetic array analysis, and high-throughput screening reveals that sumoylation of Mcm21p promotes disassembly of the mitotic spindle.
Journal ArticleDOI
Hippocampal-prefrontal engagement and dynamic causal interactions in the maturation of children's fact retrieval
Soohyun Cho,Arron W.S. Metcalfe,Christina B. Young,Srikanth Ryali,David C. Geary,Vinod Menon +5 more
TL;DR: This study highlights the contribution of hippocampal–prefrontal circuits to the early development of retrieval fluency in arithmetic problem solving and provides a novel framework for studying dynamic developmental processes that accompany children's development of problem-solving skills.
Proceedings ArticleDOI
Work smart, not hard: Recalling relevant experiences for vast-scale but time-constrained localisation
TL;DR: During localisation, the loading of past experiences are prioritised in a probabilistic way and it is shown that this memory policy significantly improves localisation efficiency, enabling long-term autonomy on robots with limited computational resources.
Proceedings ArticleDOI
Addressing the straggler problem for iterative convergent parallel ML
Aaron Harlap,Henggang Cui,Wei Dai,Jinliang Wei,Gregory R. Ganger,Phillip B. Gibbons,Garth A. Gibson,Eric P. Xing +7 more
TL;DR: FlexRR provides a scalable, efficient solution to the straggler problem for iterative machine learning (ML) and consistently observe near-ideal run-times (relative to no performance jitter) across all real and injected straggle behaviors tested.
Journal ArticleDOI
Regression DCM for fMRI
Stefan Frässle,Ekaterina I. Lomakina,Adeel Razi,Karl J. Friston,Joachim M. Buhmann,Klaas E. Stephan +5 more
TL;DR: The results indicate that rDCM represents a computationally highly efficient approach with promising potential for inferring whole‐brain connectivity from individual fMRI data and a variational Bayesian inversion method that enables extremely fast inference and accelerates model inversion by several orders of magnitude compared to classical DCM.