Results 41 to 50 of about 215,679 (256)

Learning on Hypergraphs with Sparsity [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Hypergraph is a general way of representing high-order relations on a set of objects. It is a generalization of graph, in which only pairwise relations can be represented. It finds applications in various domains where relationships of more than two objects are observed.
Nguyen, Canh Hao, Mamitsuka, Hiroshi
openaire   +4 more sources

Sparse Multi-View K-Means Clustering

IEEE Access
In machine learning, k-means clustering is an unsupervised leaning technique to partition the data into k clusters that are homogeneous within the cluster and heterogeneous between clusters.
Miin-Shen Yang, Shazia Parveen
doaj   +1 more source

Exploration under sparsity constraints [PDF]

2015 European Conference on Mobile Robots (ECMR), 2015
This paper addresses the problem of designing an efficient exploration strategy for multiple mobile agents. As an exploration strategy, an intelligent waypoint generation is considered, where the trajectory of the agent is governed by the properties of the explored phenomenon.
Manss, Christoph, Shutin, Dmitriy, Viseras Ruiz, Alberto, Wiedemann, Thomas, Müller, Joachim   +4 more
openaire   +2 more sources

Carcinomas and Carcinoid Tumors of the Lungs and Bronchi in Children and Adolescents: The EXPeRT Recommendations

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Primary lung carcinomas and bronchial carcinoid tumors (BC) are very rare malignancies in childhood. While typical BC and mucoepidermoid carcinomas are mostly low‐grade, localized tumors with a more favorable prognosis than in adults, necessitating avoidance of overtreatment, adenocarcinomas of the lung are often diagnosed at advanced disease ...
Michael Abele, Calogero Virgone, Michaela Kuhlen, Sabine Irtan, Yves Reguerre, Malgorzata Krawczyk, Ewa Bien, Tal Ben‐Ami, Maja Cesen, Ricardo Lopez‐Almaraz, Andrea Ferrari, Gianni Bisogno, Dominik T. Schneider, Abbas Agaimy, Constantin Lapa, Hubert Ducou le Pointe, Rainer Claus, Catherine Daniel, Ines B. Brecht, Daniel Orbach   +19 more
wiley   +1 more source

Sparse Signal Processing Concepts for Efficient 5G System Design

, 2015
As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of ...
Boche, Holger, Jung, Peter, Strohmer, Thomas, Wunder, Gerhard   +3 more
core   +1 more source

Greedy sparsity-constrained optimization [PDF]

2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011
Sparsity-constrained optimization has wide applicability in machine learning, statistics, and signal processing problems such as feature selection and compressive Sensing. A vast body of work has studied the sparsity-constrained optimization from theoretical, algorithmic, and application aspects in the context of sparse estimation in linear models ...
Bahmani, Sohail, Raj, Bhiksha, Boufounos, Petros   +2 more
openaire   +2 more sources

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen, Calogero Virgone, Antje Redlich, Michael Abele, Ricardo Lopez‐Almaraz, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Maja Mazic Cesen, Andrea Ferrari, Malgorzata A. Krawczyk, Yves Reguerre, Dominik T. Schneider, Ines B. Brecht, Charlotte Rigaud, Bilgehan Yalcin, Rainer Claus, Christian Vokuhl, Constantin Lapa, Jörg Fuchs, Segolene Hescot, Thomas Walter, Julien Hadoux, Daniel Orbach   +23 more
wiley   +1 more source

A Systematic Survey of Sparse Clustering

IEEE Access
Handling a vast amount of high-dimensional data has always been challenging. The advancement of computer technology has led to an exponential growth of accumulated information where storing and processing are to be carefully handled since not all ...
Josephine Bernadette M. Benjamin, Miin-Shen Yang   +1 more
doaj   +1 more source

RULE-BASED APPROACH FOR CONTEXT-AWARE COLLABORATIVE RECOMMENDER SYSTEM

Jordanian Journal of Computers and Information Technology, 2022
Sparsity is a serious problem of collaborative recommendation approach that has a considerable effect on recommendation quality. Contextual information is introduced in traditional recommendation systems besides users and items information to reduce ...
Soulef Benhamdi, abdesselam babouri, Raja Chiky, Jamal Nebhen   +3 more
doaj   +1 more source

C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework

, 2010
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an L1-regularized linear regression problem, commonly referred to as Lasso or Basis Pursuit.
Eldar, Yonina, Ramírez, Ignacio, Sapiro, Guillermo, Sprechmann, Pablo   +3 more
core   +4 more sources