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Constrained clustering with a complex cluster structure

Marek Śmieja, Magdalena Wiercioch
2016 Advances in Data Analysis and Classification  
In this contribution we present a novel constrained clustering method, Constrained clustering with a complex cluster structure (C4s), which incorporates equivalence constraints, both positive and negative  ...  The advantage of our algorithm increases when we are focusing on finding partitions with complex structure of clusters.  ...  creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a  ... 
doi:10.1007/s11634-016-0254-x fatcat:eqtrgzcyw5datgxuiyapdrusui

Calculating carbon nanotube–catalyst adhesion strengths

Peter Larsson, J. Andreas Larsson, Rajeev Ahuja, Feng Ding, Boris I. Yakobson, Haiming Duan, Arne Rosén, Kim Bolton
2007 Physical Review B  
Representing a cluster by a single atom or ring gives the correct trends in SWNT-cluster adhesion strengths ͑FeϷ CoϾ Ni͒, but the single-atom model yields incorrect minimum-energy structures for all three  ...  Density-functional theory is used to assess the validity of modeling metal clusters as single atoms or rings of atoms when determining adhesion strengths between clusters and single-walled carbon nanotubes  ...  FIG. 4 . 4 ͑Color online͒ Structures of a ͑5,5͒ SWNT bonded to ͑ a Ni atom, ͑b͒ the constrained Ni 10 ring top site, ͑c͒ the constrained Ni 10 ring middle site, and ͑d͒ a Ni 55 cluster.  ... 
doi:10.1103/physrevb.75.115419 fatcat:exwxr4khprb35hn62i2ogcrzia

PRosettaC: Rosetta based modeling of PROTAC mediated ternary complexes [article]

Daniel Zaidman, Nir London
2020 bioRxiv   pre-print
A structural model of this ternary complex could in principle inform rational PROTAC design.  ...  Unfortunately, only a handful of structures are available for such complexes, necessitating tools for their modeling.  ...  Rocco Moretti and Steven Lewis for much help with algorithmic details. N.L. is the incumbent of the Alan and Laraine  ... 
doi:10.1101/2020.05.27.119354 fatcat:nz2vmfwvsrg5nfbnwjnxnun36q

Structural properties of metal-benzene, Mn(benzene)m, M=Ni, V complexes: an ab initio study

George E Froudakis, Antonis N Andriotis, Madhu Menon
2001 Chemical Physics Letters  
Structural properties of metal-benzene, M n ðbenzeneÞ m , M ¼ Ni, V complexes: an ab initio study Abstract Interactions of Ni and V with benzene (Bz)-molecules are investigated using ab initio methods  ...  The differences in the behavior for Ni and V is found to be consistent with their similar contrasting bonding behavior found in interactions with graphite, C 60 and carbon nanotubes. Ó  ...  Instead a new structure, namely the Zor step-like, appears in some complexes to be either more favorable or competing with the oyster structure.  ... 
doi:10.1016/s0009-2614(01)01224-6 fatcat:7vt6xo37n5dithnd5ktj2ep5qi

Active block diagonal subspace clustering

Ziqi Xie, Lihong Wang
2021 IEEE Access  
(b) 5 nodes with the same label (c) 10 must-links. with BDR, and explore the constrained BDR without the help of structure regularizer in the SBDR. C.  ...  [29] proposed a constrained SBDR subspace clustering algorithm.  ... 
doi:10.1109/access.2021.3087575 fatcat:pkw4b2npdvb2zc3crj5yyk3iuy

XML Documents Clustering Using Tensor Space Model -- A Preliminary Study

Sangetha Kutty, Richi Nayak, Yuefeng Li
2010 2010 IEEE International Conference on Data Mining Workshops  
the enriched document representation with both the structure and the content information.  ...  A hierarchical structure is used to represent the content of the semi-structured documents such as XML and XHTML.  ...  The complexity becomes worse when dealing with large-sized datasets. There has been an attempt [7] to use a BitCube representation to cluster and query the XML documents.  ... 
doi:10.1109/icdmw.2010.106 dblp:conf/icdm/KuttyNL10 fatcat:xtmoxebrrfcfrb6d7ajuqmdc3u

Community structure detection in complex networks with partial background information

Zhong-Yuan Zhang
2013 Europhysics letters  
Constrained clustering has been well-studied in the unsupervised learning society.  ...  However, how to encode constraints into community structure detection, within complex networks, remains a challenging problem.  ...  Introduction Evidences have shown that there are often modules or community structures in complex networks [1] .  ... 
doi:10.1209/0295-5075/101/48005 fatcat:fk2r57snqfd3zmgbmlx7tsygca

High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching

Min Xu, Martin Beck, Frank Alber
2012 Journal of Structural Biology  
As a proof of principle, we can demonstrate that the automatic method can successfully classify a large number of experimental subtomograms without the need of a reference structure.  ...  Building on previous work, here we propose a fast rotational alignment method that uses the Fourier equivalent form of a popular constrained correlation measure that considers missing wedge corrections  ...  F.A. is a Pew Scholar in Biomedical Sciences, supported by the Pew Charitable Trusts.  ... 
doi:10.1016/j.jsb.2012.02.014 pmid:22420977 pmcid:PMC3821800 fatcat:ybvilvisajfs5p4idcnlflzcae

XML Documents Clustering Using a Tensor Space Model [chapter]

Sangeetha Kutty, Richi Nayak, Yuefeng Li
2011 Lecture Notes in Computer Science  
This paper introduces a novel method of representing XML documents in a Tensor Space Model (TSM) and then utilizing it for clustering.  ...  the enriched document representation of both structure and content information.  ...  with semantically annotated tags to perform the clustering task. This dataset contains a very large number of documents with deeper structure and a high branching factor.  ... 
doi:10.1007/978-3-642-20841-6_40 fatcat:gmdrv3onzrcqbesezozsn7zkdu

Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure

Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru Miyano
2010 Journal of machine learning research  
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-structure.  ...  To extend its feasibility, we propose to divide the super-structure into several clusters and perform an optimal search on each of them.  ...  This is because the complexity depends on the number of cluster edges in Algorithm 4; therefore, it is faster to always manipulate a cluster with a small number of cluster edges.  ... 
dblp:journals/jmlr/KojimaPIM10 fatcat:gttbmttqpfdldgeunlbctmb74a

Fronthaul-constrained cloud radio access networks: insights and challenges

Mugen Peng, Chonggang Wang, Vincent Lau, H. Vincent Poor
2015 IEEE wireless communications  
The fronthaul in such networks, defined as the transmission link between a baseband unit (BBU) and a remote radio head (RRH), requires high capacity, but is often constrained.  ...  clustering, and resource allocation optimization, are discussed.  ...  to optimize the performance under a fully centralized structure with constrained fronthaul.  ... 
doi:10.1109/mwc.2015.7096298 fatcat:e3622ak3kzfgzagzpouc37imi4

On the Complexity of Additive Clustering Models

Michael D. Lee
2001 Journal of Mathematical Psychology  
Among other things, these investigations show that, for a fixed number of clusters, a model with a strictly nested cluster structure is the least complicated, while a model with a partitioning cluster  ...  Using this measure, a preliminary investigation is made of the various properties of cluster structures that affect additive clustering model complexity.  ...  In the special case of a partitioning cluster structure, with clusters encompassing a, b, ..., x pairs of stimuli, the addition of the universal cluster increases the complexity measure ab } } } x by a  ... 
doi:10.1006/jmps.1999.1299 pmid:11178926 fatcat:eo536ybibjcebihhluhsenxlsa

Enhanced Community Structure Detection in Complex Networks with Partial Background Information [article]

Zhong-Yuan Zhang and Kai-Di Sun and Si-Qi Wang
2013 arXiv   pre-print
Community structure detection in complex networks is important since it can help better understand the network topology and how the network works.  ...  However, there is still not a clear and widely-accepted definition of community structure, and in practice, different models may give very different results of communities, making it hard to explain the  ...  than spectral clustering for the LFR networks, whose structures are more complex.  ... 
arXiv:1210.2473v2 fatcat:uizgu3qfxzcr5jftecukgg2jya

Ultra-high resolution structure of high-potential iron-sulfur protein

Yu Hirano, Kazuki Takeda, Kazuo Kurihara, Taro Tamada, Kunio Miki
2014 Acta Crystallographica Section A: Foundations and Advances  
High-potential iron-sulfur protein (HiPIP) possesses a Fe4S4 cluster which exhibits +2/+3 redox states and acts as an electron carrier from cytochrome bc1 complex to the reaction center complex in photosynthetic  ...  Refinement of multipolar parameters was applied to atoms of single conformational residues, water molecules with two hydrogen atoms, and the Fe4S4 cluster.  ...  High-potential iron-sulfur protein (HiPIP) possesses a Fe4S4 cluster which exhibits +2/+3 redox states and acts as an electron carrier from cytochrome bc1 complex to the reaction center complex in photosynthetic  ... 
doi:10.1107/s2053273314087981 fatcat:qzyrmxvpqjg65ofvxqvgodf7ti

Distributed Spectrum-Aware Clustering in Cognitive Radio Sensor Networks [article]

Huazi Zhang, Zhaoyang Zhang, Huaiyu Dai, Rui Yin, Xiaoming Chen
2014 arXiv   pre-print
The spectrum-aware clustered structure is presented where the communications consist of intra-cluster aggregation and inter-cluster relaying.  ...  In order to save communication power, the optimal number of clusters is derived and the idea of groupwise constrained clustering is introduced to minimize intra-cluster distance under spectrum-aware constraint  ...  In recent years, a branch of constrained clustering algorithms have been developed to cluster instances with pairwise constraints, such as constrained K-means [13] and constrained complete-link clustering  ... 
arXiv:1402.5488v1 fatcat:pxig4yulx5dr7phpuyy63hklzu
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