Statistical inference on graphs - Biau, Bleakley - 2006G. Biau and K. Bleakley. Statistical inference on graphs. Statistics & Decisions, 24(2):209-232, 2006.Frank, O. (1971). Statistical Inference in Graphs. Stockholm, FOA Repro Forsvarets Forskningsanstalk.G. Biau and L. Bleakley. ...
17 国际基础科学大会-The betti number of the independence complex of tenary graphs-Hehui Wu 1:00:20 国际基础科学大会-On equivalence relations induced by Polish groups-Longyun Ding 49:38 国际基础科学大会-Reverse engineering structural connectivity in brain networks 1:03:19 国际基础科学大会-Dynamics...
02 Torsion points and concurrent lines on Del Pezzo surfaces of degree one 58:59 Applications of optimal transportation in causal inference 1:02:02 The Emergence of Spatial Patterns for Diffusion-Coupled Compartments with Activa 58:24 Agent-based models_ from bacterial aggregation to wealth hot-...
We propose a framework for massive-scale training of kernel-based statistical models, based on combining distributed convex optimization with randomization... H Avron,V Sindhwani - 《Technometrics》 被引量: 25发表: 2015年 Computer Age Statistical Inference: Sparse Modeling and the Lasso We then loo...
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detai...
“link prediction” with little interaction with the rest of network analysis (notable exceptions are the works of Clauset et al.49and Guimerá et al.48, who framed link prediction as a statistical inference problem, based on generative network models). Decomposing a problem into separate sub...
Supervised variational model with statistical inference and its application in medical image segmentation. Li C Y;Wang X Y;Eberl S;.Supervised variational model with statistical inference and its application in medical image segmentation.IEEE Transactions on B ... Changyang,Li,Xiuying,... - IEEE ...
Maximum likelihood estimation (MLE) is an inference framework for finding the best statistical estimates of model parameters from historical training data. Using MLE, the loss function estimates how closely the distribution of predictions made by a model matches the distribution of target variables in ...
In summary, we derived a formal statistical test for the differential network analysis based on the inference of GGM, as well as a multiple testing procedure for simultaneously testing the large number of tests with FDR control to infer the structure of the differential network. Through simulation...
b.the mathematical study of the theoretical nature of such distributions and tests. See alsodescriptive statistics,statistical inference [C18 (originally 'science dealing with facts of a state'): via GermanStatistik, from New Latinstatisticusconcerning state affairs, from Latinstatusstate] ...