Results 91 to 100 of about 117,362 (280)

Graphs with regular monoids

open access: yesDiscrete Mathematics, 2003
The author proves that the endomorphism monoid of \(\overline{C_n}\) \((n\geq 3)\) is regular where \(\overline{C_n}\) denotes the complement graph of a undirected cycle of \(n\) vertices. It is noted that \(\text{End}(\overline{C_6})\) is not an orthodox monoid.
openaire   +1 more source

Matchings in regular graphs

open access: yesDiscrete Mathematics, 1981
AbstractWe consider k-regular graphs with specified edge connectivity and show how some classical theorems and some new results concerning the existence of matchings in such graphs can be proved by using the polyhedral characterization of Edmonds.
Denis Naddef, William R. Pulleyblank
openaire   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

Application of Non-Sparse Manifold Regularized Multiple Kernel Classifier

open access: yesMathematics
Non-sparse multiple kernel learning is efficient but not directly able to be applied in a semi-supervised scenario; therefore, we extend it to semi-supervised learning by using a manifold regularization.
Tao Yang
doaj   +1 more source

Alzheimer's Disease Risk Factor APOE4 Exerts Dimorphic Effects on Female Bone

open access: yesAdvanced Science, EarlyView.
In aging bone, osteocytes accumulate neurodegenerative risk factor Apolipoprotein E (APOE). A humanized version of the Alzheimer's disease risk allele APOE4 altered the mouse bone transcriptome and proteome, with effects in female bone surpassing the brain, including bone fragility due to suppressed osteocytic maintenance of bone quality, identifying ...
Charles A. Schurman   +15 more
wiley   +1 more source

Domain-Invariant Label Propagation With Adaptive Graph Regularization

open access: yesIEEE Access
As an effective machine learning paradigm, domain adaptation (DA) learning aims to enhance the learning performance of the target domain by utilizing other relevant but distinct domain(s) (referred to as the source domain(s)).
Yanning Zhang, Jianwen Tao, Liangda Yan
doaj   +1 more source

TorusE: Knowledge Graph Embedding on a Lie Group

open access: yes, 2017
Knowledge graphs are useful for many artificial intelligence (AI) tasks. However, knowledge graphs often have missing facts. To populate the graphs, knowledge graph embedding models have been developed.
Ebisu, Takuma, Ichise, Ryutaro
core   +1 more source

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment

open access: yesAdvanced Science, EarlyView.
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng   +17 more
wiley   +1 more source

Classification of graphs by regularity

open access: yesJournal of Combinatorial Theory, Series B, 1981
AbstractWe give a classification of graphs by two parameters s and t such that a graph is regular iff t ≥ 2, edge-regular iff t ≥ 3, and distance regular of diameter δ iff s = δ, t ≥ 2δ − 2. We investigate the algebra of polynomials in the adjacency matrix and relate to every graph a family of orthogonal polynomials. This generalizes various results on
openaire   +2 more sources

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

open access: yesAdvanced Science, EarlyView.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong   +9 more
wiley   +1 more source

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