Results 11 to 20 of about 691,873 (239)
Variable Selection and Parameter Tuning in High-Dimensional Prediction [PDF]
, 2010 In the context of classification using high-dimensional data such as microarray gene expression data, it is often useful to perform preliminary variable selection.
Bernau, Christoph +1 more
core +1 more source
A precision study of the fine tuning in the DiracNMSSM [PDF]
, 2013 Recently the DiracNMSSM has been proposed as a possible solution to reduce the fine tuning in supersymmetry. We determine the degree of fine tuning needed in the DiracNMSSM with and without non-universal gaugino masses and compare it with the fine tuning
A Arvanitaki +91 more
core +2 more sources
Persistent Homology in Sparse Regression and its Application to Brain Morphometry [PDF]
, 2015 Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system.
Chung, Moo K. +4 more
core +2 more sources
Parameter-tuning Networks: Experiments and Active Walk Model
, 2008 The tuning process of a large apparatus of many components could be represented and quantified by constructing parameter-tuning networks. The experimental tuning of the ion source of the neutral beam injector of HT-7 Tokamak is presented as an example ...
Han, Xiao-Pu +3 more
core +1 more source
Towards Self-Tuning Parameter Servers [PDF]
2020 IEEE International Conference on Big Data (Big Data), 2020 Recent years, many applications have been driven advances by the use of Machine Learning (ML). Nowadays, it is common to see industrial-strength machine learning jobs that involve millions of model parameters, terabytes of training data, and weeks of training. Good efficiency, i.e., fast completion time of running a specific ML job, therefore, is a key
Liu, Chris +6 more
openaire +2 more sources
Naturalness of Neutralino Dark Matter
, 2013 We investigate the level of fine-tuning of neutralino Dark Matter below 200 GeV in the low-energy phenomenological minimal supersymmetric Standard Model taking into account the newest results from XENON100 and the Large Hadron Collider as well as all ...
Grothaus, Philipp +2 more
core +1 more source
Robust Tuning Datasets for Statistical Machine Translation
, 2017 We explore the idea of automatically crafting a tuning dataset for Statistical Machine Translation (SMT) that makes the hyper-parameters of the SMT system more robust with respect to some specific deficiencies of the parameter tuning algorithms.
Nakov, Preslav, Vogel, Stephan
core +1 more source
FEBS Letters, EarlyView.We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +1 more source
Molecular Oncology, EarlyView.Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice +16 more
wiley +1 more source
Parameter Tuning Using Gaussian Processes [PDF]
, 2012 Most machine learning algorithms require us to set up their parameter values before applying these algorithms to solve problems. Appropriate parameter settings will bring good performance while inappropriate parameter settings generally result in poor ...
Ma, Jinjin
core +1 more source