Results 81 to 90 of about 49,338 (223)
Innovation Pursuit: A New Approach to Subspace Clustering
, 2017 In subspace clustering, a group of data points belonging to a union of subspaces are assigned membership to their respective subspaces. This paper presents a new approach dubbed Innovation Pursuit (iPursuit) to the problem of subspace clustering using a ...
Atia, George, Rahmani, Mostafa
core +1 more source
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit
, 2016 Subspace clustering methods based on $\ell_1$, $\ell_2$ or nuclear norm regularization have become very popular due to their simplicity, theoretical guarantees and empirical success.
Robinson, Daniel P. +2 more
core +1 more source
The Anatomical Record, EarlyView.Abstract Geometric morphometric analyses are used to explore variation of maxillary dental arcades of Australopithecus afarensis, expanding on the work of Hanegraef and Spoor, 2025 (Morphological variation of the Australopithecus afarensis maxilla.
Hester Hanegraef +2 more
wiley +1 more source
Graph Connectivity in Noisy Sparse Subspace Clustering [PDF]
, 2016 Subspace clustering is the problem of clustering data points into a union of low-dimensional linear/affine subspaces. It is the mathematical abstraction of many important problems in computer vision, image processing and machine learning.
Singh, Aarti +2 more
core +1 more source
A Guide to Bayesian Optimization in Bioprocess Engineering
Biotechnology and Bioengineering, EarlyView.ABSTRACT Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small data sets, and provide adaptive suggestions for sequential experimentation.
Maximilian Siska +5 more
wiley +1 more source
Thalamic connectivity mirrors spatial maps of network dysfunction in nonlesional focal epilepsy
Epilepsia, EarlyView.Abstract Objective Focal epilepsy is increasingly conceptualized as a network disorder, yet the extent to which network dysfunction reflects a shared phenotype remains unknown. Spatially conserved patterns of network dysfunction may implicate a centralized mechanism underlying widespread impairment.
Joline M. Fan +7 more
wiley +1 more source
Low-Rank Tensor Thresholding Ridge Regression
IEEE Access, 2019 In the area of subspace clustering, methods combining self-representation and spectral clustering are predominant in recent years. For dealing with tensor data, most existing methods vectorize them into vectors and lose most of the spatial information ...
Kailing Guo +3 more
doaj +1 more source
Subspace clustering via thresholding and spectral clustering [PDF]
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 ICASSP ...
Heckel, Reinhard, Bölcskei, Helmut
openaire +2 more sources
Epilepsia Open, EarlyView.Abstract Objective Characterize electroencephalogram (EEG) dynamics during propofol withdrawal in patients with generalized convulsive status epilepticus (GCSE) and explore their association with functional outcomes. Methods We conducted a retrospective cohort study of adult patients with GCSE who received continuous EEG monitoring and propofol ...
Mathieu Dhoisne +5 more
wiley +1 more source
Subspace Clustering of Subspaces: Unifying Canonical Correlation Analysis and Subspace Clustering
19 pages, Submitted to IEEE Transactions on Signal ...
Karakasis, Paris A. +1 more
openaire +2 more sources