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Density peaks clustering algorithm based on weighted k-nearest neighbors and geodesic distance

Lina Liu, Donghua Yu
2020 IEEE Access  
Therefore, a major motivation of this paper is to extend the DPC to manifold datasets to expand the scope of application, and improve the clustering performance on manifold and non-manifold datasets.  ...  In 2014, density peaks clustering (DPC) was proposed by Rodriguez and Laio [8] , resulting in density-based clustering algorithms attracting wider attention and application.  ...  The experimental results on artificial and real-world datasets, including image datasets, show that the DPC-WKNN-GD improves the clustering performance and significantly outperforms comparison algorithms  ... 
doi:10.1109/access.2020.3021903 fatcat:drlskzss5jf23noasb6bkbzsgi

High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping

Xin Li, Liam Collins, Keisuke Miyazawa, Takeshi Fukuma, Stephen Jesse, Sergei V. Kalinin
2018 Nature Communications  
To meet this challenge, we present a data-driven approach, Graph-Bootstrapping, based on low-dimensional manifold learning of the full SPM spectra and demonstrate its successes for high-veracity mechanical  ...  mapping on a mixed polymer thin film and resolving irregular hydration structure of calcite at atomic resolution.  ...  The authors gratefully acknowledge Hagen Söngen and Angelika Kühnle for help and discussion on 3D-AFM datasets.  ... 
doi:10.1038/s41467-018-04887-1 pmid:29930246 pmcid:PMC6013493 fatcat:irlqbqp53zbgjfn5h6xhoierna

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Jing An, Ping Ai, Cong Liu, Sen Xu, Dakun Liu
2021 IEEE Access  
The most remarkable applications are based on the fault diagnosis classification model.  ...  Then, based on the representation learned from the autoencoders, the local manifold learning method UMAP is used to search for more clustering manifold structures.  ...  This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.  ... 
doi:10.1109/access.2021.3059459 fatcat:hirjpl7c2bbz3a5nhut6rxiuae

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results [article]

Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet (+16 others)
2022 arXiv   pre-print
The competition asked participants to provide implementations of machine learning algorithms on manifolds that would respect the API of the open-source software Geomstats (manifold part) and Scikit-Learn  ...  This paper describes the design of the challenge and summarizes its main findings.  ...  In tandem with a sampling module, we could consider extending Geomstats' probability module that provides probability densities on manifolds.  ... 
arXiv:2206.09048v1 fatcat:ghgwtpjqyzhrxmco7bk24satuy

Fundamentals [chapter]

Michael Christoph Thrun
2018 Projection-Based Clustering through Self-Organization and Swarm Intelligence  
., 1990] can be used to define neighborhoods based on density.  ...  ., 2000] or local linear embedding (LLE) [Roweis/Saul, 2000] that are designed to find a manifold 5 that represents a given set of high-dimensional data 6 are called manifold learning methods.  ... 
doi:10.1007/978-3-658-20540-9_2 fatcat:fgrf47vxvfa6bir43hbxjvmlce

Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning

Guang Yang, Xin Li, Yongqiang Cheng, Mingchao Wang, Dong Ma, Alexei P. Sokolov, Sergei V. Kalinin, Gabriel M. Veith, Jagjit Nanda
2021 Nature Communications  
To project the high dimensional TERS imaging to a two-dimensional manifold space and categorize amorphous silicon structure, we developed a multiresolution manifold learning algorithm.  ...  However, short-range atomic ordering quantification and nanoscale spatial resolution over a large area on a-Si have remained major challenges and practically unexplored.  ...  The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/ doe-public-access-plan).  ... 
doi:10.1038/s41467-020-20691-2 pmid:33495465 fatcat:amvuy7dy5vhahd4pxpxwfjc7xe

Beyond Sentiment: The Manifold of Human Emotions [article]

Seungyeon Kim, Fuxin Li, Guy Lebanon, Irfan Essa
2013 arXiv   pre-print
Besides obtaining significant improvements over a baseline without manifold, we are also able to visualize different notions of positive sentiment in different domains.  ...  We investigate the resulting model, compare it to psychological observations, and explore its predictive capabilities.  ...  Our fitted model bears close similarities to models developed within the psychological literature, based on human survey data.  ... 
arXiv:1202.1568v2 fatcat:z5mifnewzzhp5ps24dyhkk6you

Interactive Exploration of Large-Scale UI Datasets with Design Maps

Luis A Leiva, Asutosh Hota, Antti Oulasvirta
2021 Interacting with computers  
Designers are increasingly using online resources for inspiration. How to best support design exploration without compromising creativity?  ...  Overall, designers find Design Maps supporting their creativity (avg.  ...  They pointed out that they would like to interact with a design space visualization based on some UI similarity.  ... 
doi:10.1093/iwcomp/iwab006 fatcat:msdbbhy52bfwpo4ry3onxhuqka

Information Geometry-Based Fuzzy-C Means Algorithm for Cooperative Spectrum Sensing

Yongwei Zhang, Canfeng Ma, Yonghua Wang, Shunchao Zhang, Pin Wan
2020 IEEE Access  
Moreover, a novel clustering algorithm, namely Riemannian distance based Fuzzyc means clustering (RDFCM) algorithm, is developed to cluster the samples on manifold for obtaining a classifier, which is  ...  Based on the information geometry (IG) theory, the covariance matrix of the signal matrix is mapped into a point on a manifold. Then, the sample points on the manifold are collected as a data set.  ...  Subsequently, the RDFCM algorithm is designed, which clustering directly on the manifold space.  ... 
doi:10.1109/access.2020.3019422 fatcat:cjvm67nbjng3de4i2qyv4zs3zy

Methods of Projection [chapter]

Michael Christoph Thrun
2018 Projection-Based Clustering through Self-Organization and Swarm Intelligence  
Thrun, Projection-Based Clustering through Self-Organization and Swarm Intelligence, https://doi.  ...  Venna et al. argued that "manifold learning methods are not necessarily good for [...] visualization [...] since they have been designed to find a manifold, not compress it into a lower dimensionality"  ...  Using transitive closure for these weighted distances allows classical clustering algorithms (AU*clustering) to actually perform distance-and density-based clustering, taking into account the complex structure  ... 
doi:10.1007/978-3-658-20540-9_4 fatcat:kmxwfd7tmrc3doylh6sij2zlfe

Machine Learning in Chemical Engineering : A Perspective

Artur M. Schweidtmann, Erik Esche, Asja Fischer, Marius Kloft, Jens-Uwe Repke, Sebastian Sager, Alexander Mitsos
2021 Chemie - Ingenieur - Technik (2021). doi:10.1002/cite.202100083  
The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio-)catalysts, and functional materials.  ...  , and (6) creativity.  ...  density estimation for applications with unknown distributions, e.g., for data smoothing [23] .  ... 
doi:10.18154/rwth-2021-09826 fatcat:7tlvcx22urd27fpjfbw4iqhr7a

Cluster Density Properties Define a Graph for Effective Pattern Feature Selection

Khadidja Henni, Neila Mezghani, Amar Mitiche
2020 IEEE Access  
The graph design in this method promotes feature relevance, downgrades redundancy, and is robust to outliers and cluster imbalances.  ...  Feature selection is a challenging problem that occurs in the high-dimensional data analysis of many major applications.  ...  The grid-based algorithm CLIQUE [44] , which developed subspace clustering, recursively investigates the set of possible subspaces based on an a priori-like method and then retains grid cells with a density  ... 
doi:10.1109/access.2020.2981265 fatcat:vmgfcfexxbavjny3ocsrbpzvrm

Advancing Performability in Playable Media: A Simulation-based Interface as a Dynamic Score

I. Choi
2014 EAI Endorsed Transactions on Creative Technologies  
Problems of designing playable media with non-game orientation are stated as the problems of designing a platform for creative explorations and creative expressions.  ...  When designing playable media with non-game orientation, alternative play scenarios to gameplay scenarios must be accompanied by alternative mechanics to game mechanics.  ...  We wish to thank Hiroki Sayama for sharing his code base to develop the playable implementation.  ... 
doi:10.4108/ct.1.1.e5 fatcat:t5fswpdrpbamzdrxfjn2ixqtfq

Foundations of Unsupervised Learning (Dagstuhl Seminar 16382)

Maria-Florina Balcan, Shai Ben-David, Ruth Urner, Ulrike Von Luxburg, Marc Herbstritt
2017 Dagstuhl Reports  
The goal of the seminar was to initiate a broader and more systematic research on the foundations of unsupervised learning with the ultimate aim to provide more support to practitioners.  ...  However, there is currently little formal guidance as to how, when and to what effect to use which unsupervised learning method.  ...  The procedure is then shown to be competitive on clustering applications, and moreover is quite stable to a wide range of settings of its tuning parameter.  ... 
doi:10.4230/dagrep.6.9.94 dblp:journals/dagstuhl-reports/BalcanBUL16 fatcat:gliqlrxzyrbzffssk5t3udw54q

Electronic structure and photophysics of a supermolecular iron complex having a long MLCT-state lifetime and panchromatic absorption

Ting Jiang, Yusong Bai, Peng Zhang, Qiwei Han, David B. Mitzi, Michael J. Therien
2020 Proceedings of the National Academy of Sciences of the United States of America  
Density functional and domain-based local pair natural orbital coupled cluster [DLPNO-CCSD(T)] theory reveal triplet-state wavefunction spatial distributions consistent with electronic spectroscopic and  ...  Here, we engineer supermolecular Fe(II) chromophores based on the bis(tridentate-ligand)metal(II)-ethyne-(porphinato)zinc(II) conjugated framework, previously shown to give rise to highly delocalized low-lying  ...  Density functional and domain-based local pair natural orbital coupled cluster [DLPNO-CCSD(T)] theory reveal tripletstate wavefunction spatial distributions consistent with electronic spectroscopic and  ... 
doi:10.1073/pnas.2009996117 pmid:32788361 fatcat:3fiqkzn7ebakjewzyrdo4uogrm
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