Results 51 to 60 of about 115,711 (260)

Graph-Based Clustering via Group Sparsity and Manifold Regularization

IEEE Access, 2019
Clustering refers to the problem of partitioning data into several groups according to the predefined criterion. Graph-based method is one of main clustering approaches and has been shown impressive performance in many literatures.
Jianyu Miao, Tiejun Yang, Junwei Jin, Lingfeng Niu   +3 more
doaj   +1 more source

Tight Distance-Regular Graphs [PDF]

Journal of Algebraic Combinatorics, 2000
We consider a distance-regular graph $\G$ with diameter $d \ge 3$ and eigenvalues $k= _0> _1>... > _d$. We show the intersection numbers $a_1, b_1$ satisfy $$ ( _1 + {k \over a_1+1}) ( _d + {k \over a_1+1}) \ge - {ka_1b_1 \over (a_1+1)^2}. $$ We say $\G$ is {\it tight} whenever $\G$ is not bipartite, and equality holds above.
Jurišić, Aleksandar, Koolen, Jack, Terwilliger, Paul   +2 more
openaire   +2 more sources

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

Advanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su, Jian Qin, Hui Shen, Ling‐Li Zeng, Baojuan Li, Jin Liu, Xuemei Song, Li Liu, Weidan Pu, Tongjian Bai, Huaning Wang, Hong Yin, Kai Wang, Lingjiang Li, Dewen Hu   +14 more
wiley   +1 more source

Zero Shot Learning with the Isoperimetric Loss

, 2019
We introduce the isoperimetric loss as a regularization criterion for learning the map from a visual representation to a semantic embedding, to be used to transfer knowledge to unknown classes in a zero-shot learning setting.
Bertozzi, Andrea, Deutsch, Shay, Soatto, Stefano   +2 more
core   +1 more source

Nim-Regularity of Graphs [PDF]

The Electronic Journal of Combinatorics, 1999
Ehrenborg and Steingrímsson defined simplicial Nim, and defined Nim-regular complexes to be simplicial complexes for which simplicial Nim has a particular type of winning strategy. We completely characterize the Nim-regular graphs by the exclusion of two vertex-induced subgraphs, the graph on three vertices with one edge and the graph on five ...
openaire   +2 more sources

Integrated Transcriptomics Reveals Evolutionary Trajectories and Cell Density‐Dependent Mechanisms in Aldosterone‐Producing Adenomas

Advanced Science, EarlyView.
Aldosterone‐producing adenomas (APAs) develop via two distinct paths: directly from adrenal zona glomerulosa (zG) cells, or stepwise from zG cells through aldosterone‐producing micronodules (APMs) before progressing to APAs. Advanced single‐cell and spatial analyses identified distinct cell states linked to oxidative stress and cell–cell interactions ...
Zhuolun Sun, Changying Jing, Martina Tetti, Siyuan Gong, Jia Wei, Yingxian Pang, Martin Reincke, Tracy Ann Williams   +7 more
wiley   +1 more source

Hyperspectral Anomaly Detection via Low-Rank Representation with Dual Graph Regularizations and Adaptive Dictionary

Remote Sensing
In a hyperspectral image, there is a close correlation between spectra and a certain degree of correlation in the pixel space. However, most existing low-rank representation (LRR) methods struggle to utilize these two characteristics simultaneously to ...
Xi Cheng, Ruiqi Mu, Sheng Lin, Min Zhang, Hai Wang   +4 more
doaj   +1 more source

Nonlinear and oblique boundary value problems for the Stokes equations

Electronic Journal of Qualitative Theory of Differential Equations, 2011
In this paper we consider the nonlinear boundary value problem governed by a stationary perturbed Stokes system with mixed boundary conditions (Dirichlet- maximal monotone graph), in a smooth domain.
Hamid Benseridi, Mourad Dilmi
doaj   +1 more source

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

, 2013
Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object.
A. O’Hagan, B. Silverman, D. Cremers, D. Cremers, D. Cremers, D. Cremers, D. Freedman, D. Freedman, D. Hunter, G. Slabaugh, J. Chang, J. Malcolm, J. Malcolm, J. Schindelin, J. Zhu-Jacquot, Joshua C. Chang, L. Grady, N. El Zehiry, N. Vu, O. Veksler, P. Das, P. Kohli, P. Viola, S. Belongie, S. Dambreville, S. Lee, S. Tabbone, S.C. Pei, T. Heimann, T. Jiang, Tom Chou, V. Lempitsky, V. Lempitsky, V. Vineet, Y. Boykov, Y. Boykov, Y. Boykov   +36 more
core   +1 more source

Learned Conformational Space and Pharmacophore Into Molecular Foundational Model

Advanced Science, EarlyView.
The Ouroboros model introduces two orthogonal modules within a unified framework that independently learn molecular representations and generate chemical structures. This design enables flexible optimization strategies for each module and faithful structure reconstruction without prompts or noise.
Lin Wang, Yifan Wu, Hao Luo, Minglong Liang, Yihang Zhou, Cheng Chen, Chris Liu, Jun Zhang, Yang Zhang   +8 more
wiley   +1 more source