ライフサイエンスコーパス: regularize

1 n be efficiently optimized and appropriately regularized.

2 n with the resolution of those that are less regularized.

3 maining residues in food products have to be regularized.

4 d so that the barrier optimization has to be regularized.

5 ency: a verb that is 100 times less frequent regularizes 10 times as fast.

6 narche, fecundability ratios for cycles that regularized 2-3 and >/=4 years after menarche were 0.90

7 rt the development and characterization of a regularized and truly modular peptide-specific binding p

8 dicates that the model must be simplified or regularized and/or that the training dataset requires au

9 development includes a metadata harvester to regularize, annotate, and preserve workflows and facilit

10 ally demonstrate the genericity of this self-regularizing anti-twist.

11 st absolute shrinkage and selection operator-regularized approach (derivation: 80% of cohort) and val

12 on testing our method on simulated data, our regularized approach requires less data and allows simul

13 These features were used to train a Bayesian regularized artificial neural network (BRANN) model to p

14 paper, we develop a biological network-based regularized artificial neural network model for predicti

15 bert spaces regressions - RKHS, and Bayesian Regularized Artificial Neural Networks - BRANN, respecti

16 Here, we present GRAPE (Graph-Regularized Attentive Protein Embeddings), a framework u

17 results show that our method outperforms non-regularized baselines, yielding up to 3% improvement in

18 Using a regularized Bayesian integration system, we provide maps

19 eatment for insomnia, the authors found that regularizing bedtimes and rise times was often sufficien

20 dy highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal inte

21 e a Bayesian method called SUBSTRA that uses regularized biclustering to identify patient subtypes an

22 The tensor completion model is then regularized by a Cartesian product graph of protein-prot

23 a nonnegative Tucker decomposition algorithm regularized by a high-order graph that captures spatial

24 y of survival prediction over the Cox models regularized by L(2) or L(1).

25 gh the sparsity constraint, which is further regularized by requiring continuity between consecutive

26 present a convolutional neural network (CNN) regularized by the graph of protein-protein interaction

27 , since the machine learning approximator is regularized by the physical law.

28 ll number of magnetic field measurements are regularized by the physics information term in the loss

29 ime where the regression problem is strongly regularized by the prior, we show that computing the mar

30 projection on latent structures (OPLS), and regularized canonical correlation analysis (rCCA) to stu

31 They also provide additional evidence that regularized canonical correlation analysis and hierarchi

32 A regularized canonical correlation analysis model was tra

33 The optimal regularized canonical correlation analysis model yielded

34 gression, canonical correlation analysis and regularized canonical correlation analysis, and use them

35 An adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) algorithm f

36 report a data integration strategy based on regularized CCA and correlation analyses of urine metabo

37 an breast cancer tissue suggest that the PPI-regularized CNN also detects spatially co-expressed gene

38 The results demonstrate that the PPI-regularized CNN constantly detects gene clusters with co

39 The flexible dropout-regularized combination approach is able to produce test

40 We apply this dropout-regularized combination approach to two clinical problem

41 The dropout-regularized combination method also generates an effecti

42 using partial knowledge of its anatomy as a regularizing constraint.

43 ng biological knowledge or data, and propose regularized covariance estimators that encourages betwee

44 The regularized covariance method efficiently computes a lar

45 Regularized Cox modeling with least absolute shrinkage a

46 We also developed a Lasso-regularized Cox proportional hazards model to predict ti

47 Elastic net regularized Cox proportional hazards models identified a

48 hese data were used to train and evaluate L2-regularized Cox proportional hazards models predicting l

49 ng models to predict GIB at 6 and 12 months: regularized Cox proportional hazards regression (RegCox)

50 e pAML training set were used to establish a regularized Cox regression model of event-free survival

51 ression-free survival (PFS) by fitting an L1-regularized Cox regression model.

52 to bipolar disorder, which included help in regularizing daily routines, or nonspecific, intensive c

53 Here, we applied entropy-regularized deconvolution (ER-DC) to cryo-ET data genera

54 oise oscillations, and ringing, by combining regularized deconvolution and Perona-Malik (PM) anisotro

55 rity and spatial information using spatially regularized deep graph networks.

56 ant), quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA, a hybrid of LDA

57 of microarray (PAM), and shrunken centroids regularized discriminant analysis (SCRDA).

58 In our framework, an iterative, voxelwise, regularized discriminant analysis is combined with a rec

59 The Laplacian-regularized discriminative model outperformed the genera

60 We provide an efficient L1-regularized discriminative training algorithm, which not

61 ns of the existing methods, we propose Graph-regularized Dual Lasso (GDL), a robust approach for eQTL

62 ough spikes are distorted by block, they are regularized during axonal propagation.

63 rsal behavior independent of the small-scale regularizing dynamics.

64 The regularizing effect is maximal for time scales on the or

65 ritized-among multiple traits based on their regularized effects.

66 e stripes and investigate their potential to regularize electrokinetic instabilities.

67 This regularized estimate is derived by flexibly combining th

68 We propose a novel method, regularized estimation of the basis covariance based on

69 For regularizing estimation and selecting relevant variables

70 We employ a regularized estimator of the correlation matrix to ensur

71 is structure consistently outperformed other regularized estimators.

72 n maximization and Q.Clear (block-sequential regularized expectation maximization with point-spread f

73 for both parameters and hyperparameters, and regularized expressions for the variance of each gene by

74 We then formulated a unified regularized factor regression (RFR) model that simultane

75 in globus pallidus; 13/23 cells in VLo), and regularized firing patterns did not always correspond to

76 ntly reduced the sAHP current and reversibly regularized firing.

77 converted into distance distributions using regularized fitting approaches.

78 gene pathway into a single score by using a regularized form of linear discriminant analysis, called

79 table model selection and efficient sparsity-regularized formulation.

80 b gene structure) of complex networks in the regularized formulation.

81 tistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association anal

82 Using a regularized Gaussian Graphical Model, we construct a tra

83 Using a regularized Gaussian graphical model, we reconstructed c

84 nnectivity features were used as inputs to a regularized generalized linear model trained to predict

85 Regularized generalized linear models (GLMs) are popular

86 ICU admission were used to train elastic-net regularized Generalized Linear Models for the prediction

87 ctive computational methods for detecting co-regularized genes that are conserved across species.

88 Regularized GGM calculated pcor between gene pairs among

89 Regularized GGM coupled with iterative random samplings

90 By making regularized GLMs more accessible and interpretable, eNet

91 ve modeling and feature identification using regularized GLMs.

92 VAE-encoded tumor transcriptome features and regularized gradient boosted decision trees (XGBoost) to

93 nature of directed networks, di-sim uses the regularized graph Laplacian and projects the rows of the

94 We present a sparse (L1 regularized) graphical model to address these challenges

95 However, regularizing hyperparameters also changed considerably,

96 ch reduce overfitting by finding appropriate regularizing hyperparameters.

97 le free minima from MD simulations using the regularized hyperspherical embeddings in latent space.

98 Our proposed L1-regularized image decomposition method and other techniq

99 Exception words are typically 'over-regularized' in SD and pronounced as they are spelled (e

100 We developed SINCERITIES (SINgle CEll Regularized Inference using TIme-stamped Expression prof

101 stimation in high-dimensional settings using regularized inference.

102 cteristic of active nematics, is in this way regularized into a laminar flow with periodic velocity o

103 ed, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7x10-12).

104 s that adding a cargo to a motor protein can regularize its gait.

105 cer, a network-regularized sparse orthogonal-regularized joint non-negative matrix factorization (NSO

106 In the last years, regularized kernel-based identification, with inspiratio

107 or sustainable development: (i) channels for regularized learning across domains of practice should b

108 We employed regularized learning methods for classifying genes speci

109 We employed regularized learning methods for discriminating gene exp

110 n the drug-drug interaction profiles and the Regularized Least Squares (RLS) classifier.

111 fficients (trained on the gold standard with regularized least squares optimization and lasso) showed

112 of CS shares strong connections with popular regularized least-squares methods, and the use of such n

113 Second, an L2-regularized least-squares problem is solved to infer val

114 A regularized least-squares regression analysis was used t

115 Regularized linear discriminant analysis indicated that

116 d from the motor cortex, a detector based on regularized linear discriminant analysis was able to ret

117 It compares favorably to a regularized linear discriminant analysis, SVMs in a one

118 age reconstruction is performed by solving a regularized linear inverse problem using the fast-iterat

119 , we investigated the use of the Constrained Regularized Linear Inversion approach as a new data proc

120 ess and ease of interpretation of multimodal regularized linear models compared to data-hungry method

121 Regularized linear models performed nearly as well as ra

122 atory relationships among genes by employing regularized linear regression (ridge regression), using

123 Regularized linear regression predicted DBPfp based on f

124 ithms employ techniques such as correlation, regularized linear regression, and conditional dependenc

125 In the setting of cooperative regularized linear regression, the method combines the l

126 set of features through [Formula: see text] regularized linear support vector machine and classifies

127 egression and kernel ridge regression with a regularized locally weighted (GRKR) method.

128 from MEDLINE abstracts and produces a set of regularized logical structures representing the meaning

129 descent framework where optimization of the regularized logistic loss function is performed with res

130 ural networks, (2) random forest, and (3) L1 regularized logistic regression (LASSO).

131 andom Forest (RF), and multi-class l(1)/l(q)-regularized logistic regression (MCRLR) for analysis and

132 e identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirno

133 outpatient contacts by means of elastic net regularized logistic regression and extreme gradient boo

134 gambiensis and habitat suitability using a regularized logistic regression and Maxent, respectively

135 xpressed genes (DEGs) as input features; (2) regularized logistic regression based on the Elastic Net

136 , which builds on a temporally smoothed l(1)-regularized logistic regression formalism that can be ca

137 l2-regularized logistic regression is accordingly adopted h

138 ng a stability selection algorithm with a L1-regularized logistic regression kernel and were then fit

139 The AUC was 0.61 (95% CI, 0.58-0.64) for the regularized logistic regression model at conception, wit

140 ict drugs and drug pairs, from which an l(2)-regularized logistic regression model is built to predic

141 ve accuracies of the top five models, the L2 regularized logistic regression model is recommended as

142 A regularized logistic regression model trained in immunoc

143 A regularized logistic regression model with fluorescence

144 Regularized logistic regression models analyzing structu

145 Using regularized logistic regression on the full dataset yiel

146 In this work, we extend l2-regularized logistic regression to the scenario of multi

147 Support vector machines and regularized logistic regression were able to identify a

148 Personalized models of regularized logistic regression, random forest, adaptive

149 ethods based on the genes pre-selected using regularized logistic regression.

150 st absolute shrinkage and selection operator regularized logistic regression.

151 Toward this end, this paper proposes a novel Regularized Low Rank-Sparse Decomposition (RegLRSD) algo

152 that can be efficiently processed by linear regularized machine learning classifiers.

153 ct 9,879 quantitative image features and use regularized machine-learning methods to select the top f

154 Recent studies have found that regularizing machine learning models to favor brain-like

155 work data are simultaneously integrated in a regularized manner.

156 The resulting algorithm, denoted soft regularized Markov clustering, is shown to outperform a

157 i are most effectively explained through the regularized mass harvesting of wild Przewalski's' horses

158 combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data an

159 We propose a soft variation of Regularized MCL (R-MCL) based on the idea of iteratively

160 , a limitation of MCL and its variants (e.g. regularized MCL) is that it only supports hard clusterin

161 Here, we uncover an inviscid regularizing mechanism stemming from self-stretching its

162 MPRAscore uses a weighted, variance-regularized method to calculate variant effect sizes rob

163 s have been shown to outperform conventional regularized methods based on compressed sensing (CS).

164 it relies on our definition of an algebraic "regularized mock modular form." As an application, we co

165 We show experimentally that given the regularized model, the inference algorithms, such as Mar

166 Our results show that deep regularized models significantly outperform shallow CNNs

167 and Zehnder as a broadly applicable tool for regularizing moduli spaces of pseudoholomorphic curves.

168 18(8): e1010438, 2022) proposed DepInfeR, a regularized multi-response regression model designed to

169 esses this gap by proposing a novel class of regularized multi-trait linear mixed models along with s

170 Our regularized multiple regression model had a high level o

171 hese high-dimensional datasets, we applied a regularized multivariate classifier to evoked potentials

172 The proposed regularized multivariate linear mixed models are relevan

173 Regularized multivariate linear regression accurately qu

174 n) in comparison with other methods based on regularized multivariate regression, probabilistic graph

175 iple holdouts and a stability criterion with regularized multivariate techniques, such as sparse part

176 We propose that the Pearson residuals from "regularized negative binomial regression," where cellula

177 ur algorithm is the only scalable method for regularized network recovery that employs Bayesian model

178 This study introduces a physics-regularized neural network (PRNN) as a computational app

179 ion via Dispersion and vAriational principle Regularized neural networks (TS-DAR), a deep learning fr

180 weights; this gain diversification strategy regularizes neuronal utilization, yoking total activity

181 l correlations between each pair of genes by regularized node-wise regression that can incorporate pr

182 eterosynaptic plasticity, the engineering of regularized noise-robust networks, and the mathematics o

183 T2 distributions were generated with a regularized non-negative least squares algorithm from mu

184 of scRNA-seq transcript counts using network-regularized non-negative matrix factorization.

185 In this article, a regularized non-negative matrix tri-factorization (R-NMT

186 have developed an integrative orthogonality-regularized nonnegative matrix factorization (iONMF) to

187 timates for closely spaced trials, betas are regularized on a voxel-wise basis using ridge regression

188 tion method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm,

189 (OMT) approach of Benamou and Brenier's, the regularized optimal mass transport (rOMT) formulates a t

190 By incorporating a regularized or "smoothed" graph into a score test, PaIRK

191 RSFC was determined for 718 regions via regularized partial correlation.

192 ffective connectivity (EC) networks based on regularized partial correlations between implanted elect

193 al low-frequency network oscillations with a regularized pattern of neuronal firing.

194 core (PRS) via 10-fold cross-validation with regularized penalized regression.

195 ve that for Ornstein-Uhlenbeck processes the regularized PFI formalism yields a unique solution in th

196 The approach uses regularized Poisson regression on tile-level accessibili

197 ra-violet cut-off, but physically meaningful regularized polaron energies are also presented.

198 his new multitask regression to structurally regularized polynomial regression to detect epistatic in

199 es prior knowledge about model parameters to regularize predictions which is important as there is am

200 with (1) a comparison of regularized vs. non-regularized procedures, (2) a null model of the degree-p

201 n of the linear reconstruction method called regularized pseudoinverse, we were able to recover high-

202 on of regions of gains and losses in a fused regularized quantile regression framework, incorporating

203 Know-GRRF embeds domain knowledge in a regularized random forest framework.

204 By developing a regularized random forest regression model, we show that

205 lem, we developed the Know-GRRF (know-guided regularized random forest) method that enables dynamic i

206 (assessed at 4 weeks) was constructed using regularized regression (ROC AUC 0.61 0.02).

207 on, implemented in C++ and OpenCL, that fits regularized regression across multiple Graphics Processi

208 A regularized regression analysis identifies key regulator

209 Regularized regression analysis is a mature analytic app

210 We used hierarchical clustering and L1 regularized regression analysis to show that transcripti

211 formance of shrinkage via neural networks to regularized regression and fine-mapping, two approaches

212 We propose a novel regularized regression approach that is based on the ada

213 e approaches generally performed better than regularized regression approaches.

214 ormalization techniques and state-of-the-art regularized regression approaches.

215 7 females; age 21.7 +/- 2), Hypothesis (H) 1:regularized regression followed by multiple regression e

216 lation group lasso algorithm using L(1)/L(2)-regularized regression for joint association analysis of

217 rior probabilities of activity are used in a regularized regression framework to predict response.

218 In the presence of high-dimensional data, regularized regression has been used as a natural strate

219 duration of breastfeeding using elastic net regularized regression in Nurses' Health Studies (n = 43

220 ed MICE approach based on an indirect use of regularized regression in terms of bias.

221 However, performance varied: regularized regression incorporating internet searches s

222 se difficulties, a previous study proposed a regularized regression method that penalizes on the diff

223 In this manuscript, we propose a multilevel regularized regression method to simultaneously identify

224 Our findings suggest that using l(2)-regularized regression methods applied to centered log-r

225 Our results showed that regularized regression methods provide better prediction

226 accuracy via comparisons with three popular regularized regression methods.

227 om a validated dataset were analyzed using a regularized regression model for characteristic selectio

228 Using elastic net regularized regression modelling, we identified key elem

229 Regularized regression models built using 5hmC densities

230 bserved that the optimum sparsity within the regularized regression models differed for each behaviou

231 strengths of logic-based network models and regularized regression models.

232 iety/depression (29 months post MRI scan) in regularized regression models.

233 gate the performance of a widely used linear regularized regression solver, known as the Elastic Net.

234 h gene as eigenSNPs and uses a novel form of regularized regression technique, termed group ridge reg

235 s compared to multiple linear regression and regularized regression techniques.

236 ICE), we investigate two approaches of using regularized regression to impute missing values of high-

237 Elastic net regularized regression was used to identify the structur

238 Regularized regression was used to select potentially pr

239 We used regularized regression with repeated cross-validation to

240 s and constructs the prediction models by L1-regularized regression with stability selection.

241 adjustment for all potential confounders via regularized regression, including ridge regression and l

242 hmark machine learning algorithms, including regularized regression, kernel-based methods, and ensemb

243 Methods of regularized regression, such as variants of the Lasso, a

244 pervised machine learning methods (including regularized regression, support vector machine and rando

245 ere we present our approach, primarily using regularized regression, which received the best-performe

246 when compared with traditional L(1)-and L(2)-regularized regression.

247 ture affective lability factor scores, using regularized regression.

248 Norepinephrine, which normally regularizes respiratory activity, renders respiratory ac

249 To address this problem, we developed regularized selection indices; the methodology integrate

250 ating the interconnections among them in the regularized selection.

251 for both dislocations and disclinations, by regularizing singularities within defect cores and so re

252 Center) wheat breeding program we show that regularized SIs derived from hyper-spectral data offer c

253 Regularized SIs offer an effective approach to leverage

254 ns the door to personalised interventions to regularize sleep-wake timing that are readily implementa

255 , suggesting that behavioral intervention to regularize sleep/wake activity might be therapeutically

256 s paper, we propose a novel procedure called regularized sliced inverse regression (RSIR) for identif

257 This result suggests that the brain regularizes slightly deviant stimuli with an asymmetry t

258 arger function space, spanned by this set of regularized solutions, than is available to conventional

259 al molecular mechanisms of cancer, a network-regularized sparse orthogonal-regularized joint non-nega

260 In the resting state, DBS is known to regularize spike activity in and downstream of the stimu

261 This penalty regularizes (stabilizes) the optimization problem, encou

262 y theories of Lighthill and Johnson, and the regularized Stokeslet method.

263 present code implementing the slender body, regularized Stokeslet, and resistive force theories; thu

264 in supporting cognitive performance, we used regularized structural equation models to predict cognit

265 ystem is problematic for existing methods of regularized supervised learning.

266 The mechanism involves regularized synaptic plasticity and an approximate match

267 utation methods, the standard t-test and the regularized t-test and ANOVA are employed in the simulat

268 %) demonstrated differential expression by a regularized t-test and stringent criteria.

269 We discuss methods using a regularized t-test based on a Bayesian statistical frame

270 The regularized t-test is less affected by missing values th

271 r we compare several methods, including SAM, regularized t-test, mixture modeling, Wilk's lambda scor

272 In this paper, we introduce a graph-regularized tensor completion model for imputing the mis

273 f Spatially-resolved transcriptomes by graph-regularized Tensor completion.

274 nctional information from MRI can be used to regularize the EEG/MEG inverse problem, giving an improv

275 The idea of shrinkage is to regularize the model parameters to reduce the effects of

276 preattentive process that uses averaging to regularize the noisy representation of position in the p

277 pre-attentive process that uses averaging to regularize the pathologically noisy representation of le

278 er-parameter optimization, ChromDMM can also regularize the smoothness of the epigenetic profiles acr

279 NMDA-type conductance to each unitary event regularized the firing but lowered the precision and rel

280 al correlation and tuning strength naturally regularizes the dimensionality of downstream computation

281 We show the new method regularizes the estimates of the fitnesses for small, re

282 logous (i.e., non-seam) contacts by which it regularizes the MT lattice.

283 Operating at this level regularizes the objective function.

284 te transfer-like and multitask approaches to regularizing the high-dimensional classification task wi

285 Instead of regularizing the problem using optimization techniques,

286 oding at the expense of spike-time coding by regularizing the spike train elicited by slow or constan

287 ffect sizes and then use cross-validation to regularize these estimates, improving prediction accurac

288 ble-exposed-infected-recovered-(SEIR) model (regularizing to avoid overfitting) and then computing th

289 n genes and (ii) linear regressions (usually regularized) to select multiple genes jointly.

290 aper presents a new method GraphTucker-graph-regularized Tucker tensor decomposition for learning hig

291 rcinoma samples of other tissue types and is regularized using a neural network model trained from ge

292 test using a Bayesian framework to compute a regularized variance of the measurements associated with

293 This paper describes an L1 regularized variational framework for developing a spati

294 o address this controversy, we implemented a regularized version of the optimal mass transport (rOMT)

295 not prevent the induction of VF, nor does it regularize VF.

296 lidate our approach with (1) a comparison of regularized vs. non-regularized procedures, (2) a null m

297 ants with C-reactive protein (CRP) >10 mg/L, regularized vs. nonregularized networks) influence resul

298 , the linear model needs to be appropriately regularized, which effectively imposes a prior on the ac

299 The proposed method is regularized with a general Lp (p in [0, 2]) penalty and

300 Compared with cycles that regularized within 2 years after menarche, fecundability