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Linear Semi-Supervised Dimensionality Reduction with Pairwise Constraint for Multiple Subclasses

Bin TONG, Weifeng JIA, Yanli JI, Einoshin SUZUKI
2012 IEICE transactions on information and systems  
In a high dimensional space, it is common that a group of data points with one class may scatter in several different groups.  ...  The manifold regularization is also incorporated in our dimensionality reduction framework. Extensive experiments on both synthetic and practical data sets illustrate the effectiveness of our method.  ...  If my enemy 'd' has a friend 'c', 'c' is an enemy of my friend 'e' and me. In these two cases, the reliabilities for the new enemy relationships are set to be 1.  ... 
doi:10.1587/transinf.e95.d.812 fatcat:t5cchlyilfbkleotnm2v7duzt4

Measuring social dynamics in a massive multiplayer online game

Michael Szell, Stefan Thurner
2010 Social Networks  
In particular we study the structure and dynamics of friend-, enemy- and communication networks.  ...  Quantification of human group-behavior has so far defied an empirical, falsifiable approach. This is due to tremendous difficulties in data acquisition of social systems.  ...  This work was supported in part by Austrian Science Fund FWF P 19132.  ... 
doi:10.1016/j.socnet.2010.06.001 fatcat:j5j2dibsmrgmdmnublwlxeukgq

Spectral clustering for link prediction in social networks with positive and negative links

Panagiotis Symeonidis, Nikolaos Mantas
2013 Social Network Analysis and Mining  
Moreover, spectral clustering compared to traditional clustering algorithms, such as k-means and DBSCAN, which assume globular (convex) regions in Euclidean space, is more flexible, in capturing the non-connected  ...  Our experimental results show that our SpectralLink algorithm outperforms the local approaches, the kmeans and two-way nCut clustering algorithms in terms of effectiveness, whereas it is more efficient  ...  is my enemy", "the friend of my enemy is my enemy", and the "enemy of my enemy is my friend".  ... 
doi:10.1007/s13278-013-0128-6 fatcat:rq5urtv3uveuxbl3ajyhff5xoy

Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer [chapter]

Tatiana Tommasi, Novi Quadrianto, Barbara Caputo, Christoph H. Lampert
2013 Lecture Notes in Computer Science  
By casting the method in the multi-view setting, we also make it possible to use different features for different databases. We call the algorithm MUST, Multitask Unaligned Shared knowledge Transfer.  ...  The evaluation is usually done within each dataset, therefore it is questionable if such results are a reliable indicator of true generalization ability.  ...  This work was supported by the PASCAL 2 Network of Excellence (TT) and by the Newton International Fellowship (NQ).  ... 
doi:10.1007/978-3-642-37331-2_1 fatcat:s7ufj7zsbvfufaigsiuj7y7xmq

Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph [article]

Chuangchuang Sun, Macheng Shen, Jonathan P. How
2020 arXiv   pre-print
The complexity of multiagent reinforcement learning (MARL) in multiagent systems increases exponentially with respect to the agent number.  ...  Through this sparsity structure, the agents can communicate in an effective as well as efficient way via only selectively attending to agents that matter the most and thus the scale of the MARL problem  ...  ACKNOWLEDGMENTS Research is supported by Scientific Systems Company, Inc. under research agreement # SC-1661-04.  ... 
arXiv:2003.01040v2 fatcat:ch3zgjpd2vcmbjpfis5nm3gglm

Deep Network Embedding for Graph Representation Learning in Signed Networks

Xiao Shen, Fu-Lai Chung
2018 IEEE Transactions on Cybernetics  
Extensive experimental results in real-world datasets demonstrate the superiority of the proposed model over the state-of-the-art network embedding algorithms for graph representation learning in signed  ...  In addition, to preserve the structural balance property of signed networks, we design the pairwise constraints to make the positively connected nodes much closer than the negatively connected nodes in  ...  both "the enemy of my enemy is my friend" and "the enemy of my enemy is my enemy" can be observed in the signed networks [12] .  ... 
doi:10.1109/tcyb.2018.2871503 pmid:30307885 fatcat:kzpu5szudfaijam6rhpeql6y3a

Node Classification in Social Networks [chapter]

Smriti Bhagat, Graham Cormode, S. Muthukrishnan
2011 Social Network Data Analytics  
A core problem is to use this information to extend the labeling so that all nodes are assigned a label (or labels).  ...  When dealing with large graphs, such as those that arise in the context of online social networks, a subset of nodes may be labeled.  ...  The balance theory is based on notions such as "the friend of my friend is my friend", "the enemy of my friend is my enemy" etc. to balance the signs on edges within a triad.  ... 
doi:10.1007/978-1-4419-8462-3_5 fatcat:rpu5xv2rlbcvbis2sckzzji5fu

Characterizing Attitudinal Network Graphs through Frustration Cloud [article]

Lucas Rusnak, Jelena Tešić
2021 arXiv   pre-print
We introduce the frustration cloud as a set of all nearest balanced states and use a graph-balancing algorithm to find all nearest balanced states in a deterministic way.  ...  In this paper, we propose to expand the measures of consensus from a single balanced state associated with the frustration index to the set of nearest balanced states.  ...  Acknowledgements: We would like to thank Data Lab alumni students Joshua Mitchell for initial implementation and graphB 1.0 proof-of-concept and Eric Hull for graphB 2.0 proof-of-concept and code release  ... 
arXiv:2009.07776v3 fatcat:azohmosfbvbdvltcjqwlp7ngwi

Characterizing attitudinal network graphs through frustration cloud

Lucas Rusnak, Jelena Tešić
2021 Data mining and knowledge discovery  
We introduce the frustration cloud as a set of all nearest balanced states and use a graph-balancing algorithm to find all nearest balanced states in a deterministic way.  ...  In this paper, we propose to expand the measures of consensus from a single balanced state associated with the frustration index to the set of nearest balanced states.  ...  If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly  ... 
doi:10.1007/s10618-021-00795-z fatcat:otqsophdvjghphjfhtcznbwv2q

Territorial Behavior of Eastern Chipmunks (Tamias Striatus): Encounter Avoidance and Spatial Time-Sharing

Thomas Getty
1981 Ecology  
The concept that the proximate object of interference competition is access to space is questioned.  ...  Their pattern of encounter avoidance with extensive spatial overlap resulted in spatial time-sharing.  ...  The average distance from each center of activity to that of the nearest neighbor is II ± 7 m in the summer, and 13 ± 2m in the fall. This is a relatively crowded group (c.f.  ... 
doi:10.2307/1936989 fatcat:tag6nq7d5ja63bisovvesjvaee

Simulation-based decision support for evaluating operational plans

Johan Schubert, Farshad Moradi, Hirad Asadi, Linus Luotsinen, Eric Sjöberg, Pontus Hörling, Anna Linderhed, Daniel Oskarsson
2015 Operations Research Perspectives  
Operational plans are described in the effects-based approach to operations concept as a set of actions and effects.  ...  The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation  ...  Acknowledgment We wish to express our thanks to Frida Hinshaw for her technical contribution to data analysis.  ... 
doi:10.1016/j.orp.2015.02.002 fatcat:n23dbn7cwvh5tlkwmumydxejby

Reconstructing networks [article]

Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini
2021 arXiv   pre-print
The discussion will be organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale  ...  Given the extent of the subject, we shall focus on the inference methods rooted in statistical physics and information theory.  ...  instance, implies that the enemy of my enemy is my friend) (Leskovec et al., 2010) , thus requiring additional constraints to the local ones we discussed.  ... 
arXiv:2012.02677v2 fatcat:2rwmpvmrqnbafcmkannssavyly

Evaluating the Effectiveness of Common Technical Trading Models [article]

Joseph Attia
2019 arXiv   pre-print
Creating original versions of popular models, like linear regression, K-Nearest Neighbor, and moving average crossovers, we can test how each model performs on the most popular stocks and largest indexes  ...  In addition, the data showed numerous trends such as a smaller short SMA period is accompanied by higher performance.  ...  K-Nearest Neighbor The KNN algorithm is one that uses and stores all available data and the classifies the new data or case based on a similarity measure or Euclidean distance on a graph.  ... 
arXiv:1907.10407v1 fatcat:ko3akslixza2xczov3g2ydjfl4

Trust on the World Wide Web: A Survey

Jennifer Golbeck
2006 Foundations and Trends® in Web Science  
Trust is required to foster successful interactions and to filter the abundance of information. In this review, we present a comprehensive survey of trust on the Web in all its contexts.  ...  People are the final group, where we look at the role of trust in web-based social networks and algorithms for inferring trust relationships.  ...  The reviews of this article were incredibly helpful, and the reviewers have my sincere gratitude. Many thanks also to Wendy Hall and James Finlay for their comments and support.  ... 
doi:10.1561/1800000006 fatcat:ph2mahwmxbcxxgh3bb662g7ney

Predicting Film Genres with Implicit Ideals

Andrew McGregor Olney
2013 Frontiers in Psychology  
We present a new approach to defining film genre based on implicit ideals. When viewers rate the likability of a film, they indirectly express their ideal of what a film should be.  ...  This finding lends experimental support to the notion that film genres are set of shifting, fuzzy, and highly contextualized psychological categories.  ...  Department of Education, through Grant R305A080594 and by the National Science Foundation, through Grant BCS-0826825, to the University of Memphis.  ... 
doi:10.3389/fpsyg.2012.00565 pmid:23423823 pmcid:PMC3573840 fatcat:qqutgrmamvfexo5po65tpmwuq4
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