Conference

, , .

KDD, Pages 1-9, .

Graph classification is a problem with practical applications in many different domains. To solve this problem, one usually calculates certain graph statistics (i.e., graph (More...)
@inproceedings{lee18-kdd-graph-attention,
   author={John Boaz Lee and Ryan A. Rossi and Xiangnan Kong},
   title={Graph Classification using Structural Attention},
   booktitle={KDD},
   year={2018},
   pages={1-9},
}
Conference

, , .

Proceedings of the 27th International Conference Companion on World Wide Web (WWW), .

This paper describes a general framework for learning Higher-Order Network Embeddings (HONE) from graph data based on network motifs. The HONE framework is highly (More...)
@inproceedings{rossi-WWW18,
   author={Ryan A. Rossi and Nesreen K. Ahmed and Eunyee Koh},
   title={Higher-Order Network Representation Learning},
   booktitle={Proceedings of the 27th International Conference Companion on World Wide Web (WWW)},
   year={2018},
}
Workshop/symposia

, , .

Proceedings of the 3rd International Workshop on Learning Representations for Big Networks (WWW BigNet), Pages 8, .

This paper presents a general graph representation learning framework called DeepGL for learning deep node and edge representations from large (attributed) graphs. In particular, DeepGL (More...)
@inproceedings{rossi-WWW18-BigNet,
   author={Ryan A. Rossi and Rong Zhou and Nesreen K. Ahmed},
   title={Deep Inductive Network Representation Learning},
   booktitle={Proceedings of the 3rd International Workshop on Learning Representations for Big Networks (WWW BigNet)},
   year={2018},
   pages={8},
}
Journal

, , .

IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Pages 1-14, .

Graphlets are induced subgraphs of a large network and are important for understanding and modeling complex networks. Despite their practical importance, graphlets have been (More...)
@inproceedings{rossi18tnnls,
   author={Ryan A. Rossi and Rong Zhou and Nesreen K. Ahmed},
   title={Estimation of Graphlet Counts in Massive Networks},
   booktitle={IEEE Transactions on Neural Networks and Learning Systems (TNNLS)},
   year={2018 (to appear)},
   pages={1-14},
}
Workshop/symposia

Giang Hoang Nguyen, , , , , .

Proceedings of the 3rd International Workshop on Learning Representations for Big Networks (WWW BigNet), .

Networks evolve continuously over time with the addition, deletion, and changing of links and nodes. Although many networks contain this type of temporal information, (More...)
@inproceedings{nguyen-WWW18,
   author={Giang Hoang Nguyen and John Boaz Lee and Ryan A. Rossi and Nesreen K. Ahmed and Eunyee Koh and Sungchul Kim},
   title={Continuous-Time Dynamic Network Embeddings},
   booktitle={Proceedings of the 3rd International Workshop on Learning Representations for Big Networks (WWW BigNet)},
   year={2018},
}

, , , , , , .

arXiv:1802.02896, .

Random walks are at the heart of many existing network embedding methods. However, such algorithms have many limitations that arise from the use of (More...)
@inproceedings{role2vec,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Rong Zhou and John Boaz Lee and Xiangnan Kong and Theodore L. Willke and Hoda Eldardiry},
   title={Learning Role-based Graph Embeddings},
   booktitle={arXiv:1802.02896},
   year={2018},
}

, , .

arXiv:1801.09303, .

This paper describes a general framework for learning Higher-Order Network Embeddings (HONE) from graph data based on network motifs. The HONE framework is highly (More...)
@inproceedings{rossi-HONE-arxiv,
   author={Ryan A. Rossi and Nesreen K. Ahmed and Eunyee Koh},
   title={HONE: Higher-Order Network Embeddings},
   booktitle={arXiv:1801.09303},
   year={2018},
}
Journal

, .

Journal of Big Data, Volume 5, Pages 14, .

Massive graphs are ubiquitous and at the heart of many real-world applications ranging from the World Wide Web to social networks. As a result, (More...)
@article{rossi2018compressing-graphs-cliques,
   author={Ryan A. Rossi and Rong Zhou},
   title={GraphZIP: A Clique-based Sparse Graph Compression Method},
   booktitle={Journal of Big Data},
   volume={5},
   number={1},
   year={2018},
   pages={14},
}
Journal

.

Knowledge Engineering Review (KER), Volume 33, Pages e1, .

Networks encode dependencies between entities (people, computers, proteins) and allow us to study phenomena across social, technological, and biological domains. These networks naturally evolve (More...)
@article{rossi2018ker,
   author={Ryan A. Rossi},
   title={Relational Time Series Forecasting},
   journal={Knowledge Engineering Review (KER)},
   volume={33},
   year={2018},
   pages={e1},
   publisher={Cambridge University Press},
}
Journal

, , , .

ACM Transactions on Intelligent Systems and Technology, Pages 1-30, .

This paper presents a platform for interactive graph mining and relational machine learning called GraphVis. The platform combines interactive visual representations with state-of-the-art graph (More...)
@article{rossi2017graphvis,
   author={Ryan A. Rossi and Nesreen K. Ahmed and Hoda Eldardiry and Rong Zhou},
   title={Interactive Visual Graph Mining and Learning},
   journal={ACM Transactions on Intelligent Systems and Technology},
   year={2018},
   pages={1-30},
}
Workshop/symposia

, , , , , , .

WiML NIPS, .

Learning a useful feature representation from graph data lies at the heart and success of many machine learning tasks such as classification, anomaly detection, (More...)
@inproceedings{ahmed17learning-attr-graphs,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Rong Zhou and John Boaz Lee and Xiangnan Kong and Theodore L. Willke and Hoda Eldardiry},
   title={Inductive Representation Learning in Large Attributed Graphs},
   booktitle={WiML NIPS},
   year={2017},
}

, , .

arXiv:1709.06075, Pages 1-8, .

Graph classification is a problem with practical applications in many different domains. Most of the existing methods take the entire graph into account when (More...)
@inproceedings{lee17-Deep-Graph-Attention,
   author={John Boaz Lee and Ryan Rossi and Xiangnan Kong},
   title={Deep Graph Attention Model},
   booktitle={arXiv:1709.06075},
   year={2017},
   pages={1-8},
}

, , , , , , .

arXiv:1709.04596, Pages 1-8, .

Random walks are at the heart of many existing deep learning algorithms for graph data. However, such algorithms have many limitations that arise from (More...)
@inproceedings{ahmed17Gen-Deep-Graph-Learning,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Rong Zhou and John Boaz Lee and Xiangnan Kong and Theodore L. Willke and Hoda Eldardiry},
   title={A Framework for Generalizing Graph-based Representation Learning Methods},
   booktitle={arXiv:1709.04596},
   year={2017},
   pages={1-8},
}

, , , , , , .

, Pages 1-8, .

Random walks are at the heart of many existing deep learning algorithms for graph data. However, such algorithms have many limitations that arise from (More...)
@inproceedings{ahmed17attrRandomWalks,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Rong Zhou and John Boaz Lee and Xiangnan Kong and Theodore L. Willke and Hoda Eldardiry},
   title={Generalizing Deep Learning in Graphs using Attributed Random Walks},
   year={2017},
   pages={1-8},
}

James P. Canning, Emma E. Ingram, Sammantha Nowak-Wolff, Adriana M. Ortiz, , , , .

International Conference on Complex Networks (CompleNet), .

To the best of our knowledge, this paper presents the first large-scale (More...)
@inproceedings{network-classification,
   author={James P. Canning and Emma E. Ingram and Sammantha Nowak-Wolff and Adriana M. Ortiz and Nesreen K. Ahmed and Ryan A. Rossi and Karl R. B. Schmitt and Sucheta Soundarajan},
   title={Network Classification and Categorization},
   booktitle={International Conference on Complex Networks (CompleNet)},
   year={2018},
}
Conference

, , , .

VLDB, Pages 1430-1441, .

We propose Graph Priority Sampling (GPS), a new paradigm for order-based reservoir sampling from massive streams of graph edges. GPS provides a general way (More...)
@inproceedings{ahmed17streams,
   author={Nesreen K. Ahmed and Nick Duffield and Theodore L. Willke and Ryan A. Rossi},
   title={On Sampling from Massive Graph Streams},
   booktitle={VLDB},
   year={2017},
   pages={1430-1441},
}

, , .

arXiv:1704.08829, Pages 1-11, .

This paper presents a general graph representation learning framework called DeepGL for learning deep node and edge representations from large (attributed) graphs. In particular, DeepGL (More...)
@inproceedings{rossi-deepGL-arxiv,
   author={Ryan A. Rossi and Rong Zhou and Nesreen K. Ahmed},
   title={Deep Feature Learning for Graphs},
   booktitle={arXiv:1704.08829},
   year={2017},
   pages={1-11},
}

, , , .

arXiv:1710.10335, Pages 1-6, .

Multi-label classification is an important learning problem with many applications. In this work, we propose a similarity-based approach for multi-label learning called SML. We (More...)
@inproceedings{rossi17-sml,
   author={Ryan A. Rossi and Nesreen K. Ahmed and Hoda Eldardiry and Rong Zhou},
   title={Similarity-based Multi-label Learning},
   booktitle={arXiv:1710.10335},
   year={2017},
   pages={1-6},
}

, , .

arXiv:1701.01772, Pages 1-14, .

Graphlets are induced subgraphs of a large network and are important for understanding and modeling complex networks. Despite their practical importance, graphlets have been (More...)
@inproceedings{rossi17graphlet-est,
   author={Ryan A. Rossi and Rong Zhou and Nesreen K. Ahmed},
   title={Estimation of Graphlet Statistics},
   booktitle={arXiv:1701.01772},
   year={2017},
   pages={1-14},
}
Conference

, , , .

PAKDD, Pages 1-12, .

Previous work in network analysis has focused on modeling the roles of nodes in graphs. In this paper, we introduce edge role discovery and (More...)
@inproceedings{ahmed2017roles,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Theodore L. Willke and Rong Zhou},
   title={Edge Role Discovery via Higher-order Structures},
   booktitle={PAKDD},
   year={2017},
   pages={1-12},
   publisher={Springer},
}

, , , .

arXiv preprint arXiv:1610.00844, .

Previous work in network analysis has focused on modeling the mixed-memberships of node roles in the graph, but not the roles of edges. We introduce the (More...)
@article{ahmed2016revisiting,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Theodore L. Willke and Rong Zhou},
   title={Revisiting Role Discovery in Networks: From Node to Edge Roles},
   journal={arXiv preprint arXiv:1610.00844},
   year={2016},
}
Workshop/symposia

, , , .

Proceedings of the AAAI PAIR (Plan, Activity, and Intent Recognition) Workshop, Pages 1-7, .

Previous work in network analysis has focused on model- ing node roles in the graph. In this work, we introduce edge role discovery and (More...)
@inproceedings{ahmed17aaai,
   author={Nesreen K. Ahmed and Ryan A. Rossi and Theodore L. Willke and Rong Zhou},
   title={A Higher-order Latent Space Network Model},
   booktitle={Proceedings of the AAAI PAIR (Plan, Activity, and Intent Recognition) Workshop},
   year={2017},
   pages={1-7},
}
Conference

, , .

Proceedings of the IEEE International Conference on BigData, Pages 586-595, .

Graphlets represent small induced subgraphs and are becoming increasingly important for a variety of applications. Despite the importance of the local subgraph (graphlet) counting (More...)
@inproceedings{ahmed16bigdata,
   author={Nesreen K. Ahmed and Theodore L. Willke and Ryan A. Rossi},
   title={Estimation of Local Subgraph Counts},
   booktitle={Proceedings of the IEEE International Conference on BigData},
   year={2016},
   pages={586-595},
}
Journal

, , , , .

Knowledge and Information Systems (KAIS), Pages 689-722, .

From social science to biology, numerous applications often rely on graphlets for intuitive and meaningful characterization of networks. While graphlets have witnessed (More...)
@article{ahmed2016kais,
   author={Nesreen K. Ahmed and Jennifer Neville and Ryan A. Rossi and Nick Duffield and Theodore L. Willke},
   title={Graphlet Decomposition: Framework, Algorithms, and Applications},
   journal={Knowledge and Information Systems (KAIS)},
   year={2016},
   pages={689-722},
}
Workshop/symposia

, , .

Proceedings of the 12th International Workshop on Mining and Learning with Graphs (MLG), Pages 1-8, .

This paper proposes Relational Similarity Machines (RSM): a fast, accurate, and flexible relational learning framework for supervised and semi-supervised learning tasks. Despite the importance (More...)
@inproceedings{rossi16rsm,
   author={Ryan A. Rossi and Rong Zhou and Nesreen K. Ahmed},
   title={Relational Similarity Machines},
   booktitle={Proceedings of the 12th International Workshop on Mining and Learning with Graphs (MLG)},
   year={2016},
   pages={1-8},
}
Conference

, .

ACM International Conference on Information and Knowledge Management (CIKM), Pages 1783-1792, .

Massively parallel architectures such as the GPU are becoming increasingly important due to the recent proliferation of data. In this paper, we propose a (More...)
@inproceedings{rossi16cikm,
   author={Ryan A. Rossi and Rong Zhou},
   title={Leveraging Multiple GPUs and CPUs for Graphlet Counting in Large Networks},
   booktitle={ACM International Conference on Information and Knowledge Management (CIKM)},
   year={2016},
   pages={1783-1792},
}

, , .

KDD BigMine, Pages 16, .

Graphlets represent small induced subgraphs and are becoming increasingly important for a variety of applications. Despite the importance of the local graphlet problem, existing (More...)
@inproceedings{ahmed16bigmine,
   author={Nesreen Ahmed and Ted Willke and Ryan A. Rossi},
   title={Exact and Estimation of Local Edge-centric Graphlet Counts},
   booktitle={KDD BigMine},
   year={2016},
   pages={16},
}
Journal

, .

Social Network Analysis and Mining (SNAM), Pages 30, .

Relational learning methods for heterogeneous network data are becoming increasingly important for many real-world applications. However, existing relational learning approaches are (More...)
@inproceedings{rossi16factorization,
   author={Ryan A. Rossi and Rong Zhou},
   title={Parallel Collective Factorization for Modeling Large Heterogeneous Networks},
   booktitle={Social Network Analysis and Mining (SNAM)},
   year={2016},
   pages={30},
}
Conference

, , , .

ICDM, Pages 1-10, .

From social science to biology, numerous applications often rely on graphlets for intuitive and meaningful characterization of networks at both the global macro-level as (More...)
@inproceedings{ahmed2015icdm,
   author={Nesreen K. Ahmed and Jennifer Neville and Ryan A. Rossi and Nick Duffield},
   title={Efficient Graphlet Counting for Large Networks},
   booktitle={ICDM},
   year={2015},
   pages={1-10},
}
Conference

, .

Proceedings of the AAAI Conference on Artificial Intelligence, Pages 4383-4384, .

This paper introduces the Interactive Relational Machine Learning (iRML) paradigm in which users interactively design relational models by specifying the various components, constraints, and (More...)
@inproceedings{rossi2016aaai,
   author={Ryan Rossi and Rong Zhou},
   title={Toward Interactive Relational Learning},
   booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
   year={2016},
   pages={4383-4384},
}
Journal

, .

SIGKDD Explor., Volume 17, Pages 37-41, .

Scientific data repositories have historically made data widely accessible to the scientific community, and have led to better research through comparisons, reproducibility, as well (More...)
@article{nr-sigkdd16,
   author={Ryan A. Rossi and Nesreen K. Ahmed},
   title={An Interactive Data Repository with Visual Analytics},
   journal={SIGKDD Explor.},
   volume={17},
   number={2},
   year={2016},
   pages={37-41},
   publisher={ACM},
}
Conference

, .

IEEE International Conference on Data Science and Advanced Analytics (DSAA), Pages 1-10, .

Relational models for heterogeneous network data are becoming increasingly important for many real-world applications. However, existing relational learning approaches are not parallel, have scalability (More...)
@inproceedings{rossi2015dsaa-pcmf,
   author={Ryan A. Rossi and Rong Zhou},
   title={Scalable Relational Learning for Large Heterogeneous Networks},
   booktitle={IEEE International Conference on Data Science and Advanced Analytics (DSAA)},
   year={2015},
   pages={1-10},
}
Conference

, .

International AAAI Conference on Web and Social Media (ICWSM), Pages 566-569, .

We present a web-based network visual analytics platform called GraphVis that combines interactive visualizations with analytic techniques to reveal important patterns and insights for (More...)
@inproceedings{ahmed-icwsm15,
   author={Nesreen K. Ahmed and Ryan A. Rossi},
   title={Interactive Visual Graph Analytics on the Web},
   booktitle={International AAAI Conference on Web and Social Media (ICWSM)},
   year={2015},
   pages={566-569},
}
Conference

, .

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), .

Network Repository (NR) is the first interactive data repository with a web-based platform for visual interactive analytics. Unlike other data repositories (e.g., UCI ML (More...)
@inproceedings{nr-aaai15,
   author={Ryan A. Rossi and Nesreen K. Ahmed},
   title={The Network Data Repository with Interactive Graph Analytics and Visualization},
   booktitle={Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI)},
   year={2015},
}
Journal

, , .

SIAM Journal on Scientific Computing (SISC), Volume 37, Pages 28, .

We present a fast, parallel maximum clique algorithm for large sparse graphs that is designed to exploit characteristics of social and information networks. The (More...)
@article{rossi2015pmc-sisc,
   author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin},
   title={Parallel Maximum Clique Algorithms with Applications to Network Analysis},
   journal={SIAM Journal on Scientific Computing (SISC)},
   volume={37},
   number={5},
   year={2015},
   pages={28},
   publisher={Society for Industrial and Applied Mathematics (SIAM)},
}
Journal

, .

IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 27, Pages 1112-1131, .

Roles represent node-level connectivity patterns such as star-center, star-edge nodes, near-cliques or nodes that act as bridges to different regions of the graph. Intuitively, (More...)
@article{rossi2015roles,
   author={Ryan A. Rossi and Nesreen K. Ahmed},
   title={Role Discovery in Networks},
   journal={IEEE Transactions on Knowledge and Data Engineering (TKDE)},
   volume={27},
   number={4},
   year={2015},
   pages={1112-1131},
   publisher={IEEE},
}
Journal

, .

Social Network Analysis and Mining, Volume 4, Pages 37, .

Given a large social or information network, how can we partition the vertices into sets (i.e., colors) such that no two vertices linked by an edge (More...)
@article{rossi2014coloring,
   author={Ryan A. Rossi and Nesreen K. Ahmed},
   title={Coloring Large Complex Networks},
   journal={Social Network Analysis and Mining},
   volume={4},
   number={1},
   year={2014},
   pages={37},
}
Conference

.

Advances in Knowledge Discovery and Data Mining (PAKDD), Pages 310-322, .

Large triangle cores represent dense subgraphs for which each edge has at least k − 2 triangles (same as cliques). This paper presents a fast algorithm (More...)
@inproceedings{rossi2014pakdd,
   author={Ryan A. Rossi},
   title={Fast Triangle Core Decomposition for Mining Large Graphs},
   booktitle={Advances in Knowledge Discovery and Data Mining (PAKDD)},
   year={2014},
   pages={310-322},
   publisher={Springer},
}
Conference

, , .

Networking, Pages 1-9, .

The topology of a network (connectivity of autonomous systems (ASes) or routers) has significant implications on the design of protocols and applications, and on the placement of (More...)
@inproceedings{rossi2013topology,
   author={Ryan A. Rossi and Sonia Fahmy and Nilothpal Talukder},
   title={A Multi-Level Approach for Evaluating Internet Topology Generators},
   booktitle={Networking},
   year={2013},
   pages={1-9},
}
Conference

, , , Mostofa A. Patwary.

Proceedings of the 23rd International Conference on World Wide Web (WWW), .

We propose a fast, parallel maximum clique algorithm for large sparse graphs that is designed to exploit characteristics of social and information networks. Despite clique’s status as (More...)
@inproceedings{rossi2014pmc-www,
   author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin and Mostofa A. Patwary},
   title={Fast Maximum Clique Algorithms for Large Graphs},
   booktitle={Proceedings of the 23rd International Conference on World Wide Web (WWW)},
   year={2014},
}
Workshop/symposia

, , .

SIAM Workshop on Network Science, Pages 1-2, .

Consider a graph G = (V, E). A k-core of G is a maximal induced subgraph of G where each vertex has degree at least (More...)
@inproceedings{rossi2013trianglecores,
   author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin},
   title={Triangle Core Decomposition and Maximum Cliques},
   booktitle={SIAM Workshop on Network Science},
   year={2013},
   pages={1-2},
}
Journal

, .

Internet Mathematics, Volume 10, Pages 188-217, .

We propose a dynamical system that captures changes to the network centrality of nodes as external interest in those nodes varies. We derive this system (More...)
@article{rossi2014dynamical,
   author={David F. Gleich and Ryan A. Rossi},
   title={A Dynamical System for PageRank with Time-Dependent Teleportation},
   journal={Internet Mathematics},
   volume={10},
   number={1-2},
   year={2014},
   pages={188-217},
}
Conference

, , , Keith Henderson.

Proceedings of the Sixth ACM International Conference on Web Search and Data Mining (WSDM), Pages 667-676, .

Given a large time-evolving graph, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model (More...)
@inproceedings{rossi2013modeling,
   author={Ryan A. Rossi and Brian Gallagher and Jennifer Neville and Keith Henderson},
   title={Modeling Dynamic Behavior in Large Evolving Graphs},
   booktitle={Proceedings of the Sixth ACM International Conference on Web Search and Data Mining (WSDM)},
   year={2013},
   pages={667-676},
   publisher={ACM},
}
Journal

, , , .

Journal of Artificial Intelligence Research (JAIR), Volume 45, Pages 363-441, .

Relational data representations have become an increasingly important topic due to the recent proliferation of network datasets (e.g., social, biological, information networks) and a corresponding increase (More...)
@article{rossi2012transforming,
   author={Ryan A. Rossi and Luke K. McDowell and David W. Aha and Jennifer Neville},
   title={Transforming Graph Data for Statistical Relational Learning},
   journal={Journal of Artificial Intelligence Research (JAIR)},
   volume={45},
   year={2012},
   pages={363-441},
   publisher={AAAI Press},
}

, .

Algorithms and Models for the Web Graph, Volume 7323, Pages 126-137, .

The importance of nodes in a network constantly fluctuates based on changes in the network structure as well as changes in external interest. We propose an (More...)
@article{rossi2012dynamic,
   author={Ryan A. Rossi and David F. Gleich},
   title={Dynamic PageRank using Evolving Teleportation},
   booktitle={Algorithms and Models for the Web Graph},
   volume={7323},
   series={Lecture Notes in Computer Science},
   editor={Anthony Bonato and Jeannette Janssen},
   year={2012},
   pages={126-137},
   publisher={Springer},
}

, , , .

arXiv preprint arXiv:1204.0033, .

Relational data representations have become an increasingly important topic due to the recent proliferation of network datasets (e.g., social, biological, information networks) and a (More...)
@article{rossi2012transforming,
   author={Rossi and McDowell and Aha and Neville},
   title={Transforming graph representations for statistical relational learning},
   journal={arXiv preprint arXiv:1204.0033},
   year={2012},
}

, .

arXiv preprint arXiv:1111.5312, .

Temporal networks are ubiquitous and evolve over time by the addition, deletion, and changing of links, nodes, and attributes. Although many relational datasets contain (More...)
@article{rossi11representations,
   author={Rossi and Neville},
   title={Representations and Ensemble Methods for Dynamic Relational Classification},
   journal={arXiv preprint arXiv:1111.5312},
   year={2011},
}

, , , Keith Henderson.

Proceedings of the 21st International Conference Companion on World Wide Web (WWW), Pages 997-1006, .

To understand the structural dynamics of a large-scale social, biological or technological network, it may be useful to discover behavioral roles representing the main connectivity patterns present (More...)
@inproceedings{rossi2012role,
   author={Ryan Rossi and Brian Gallagher and Jennifer Neville and Keith Henderson},
   title={Role-Dynamics: Fast Mining of Large Dynamic Networks},
   booktitle={Proceedings of the 21st International Conference Companion on World Wide Web (WWW)},
   year={2012},
   pages={997-1006},
}
Conference

, .

PAKDD, Pages 1-13, .

Relational networks often evolve over time by the addition, deletion, and changing of links, nodes, and attributes. However, accurately incorporating the full range of temporal dependencies (More...)
@inproceedings{rossi2012dynamic-srl,
   author={Ryan Rossi and Jennifer Neville},
   title={Time-evolving Relational Classification and Ensemble Methods},
   booktitle={PAKDD},
   year={2012},
   pages={1-13},
   publisher={Springer},
}
Workshop/symposia

, .

SIGKDD SOMA, Pages 89-97, .

Textual analysis is one means by which to assess communication type and moderate the influence of network structure in predictive models of individual behavior. (More...)
@inproceedings{rossi2010modeling,
   author={Ryan Rossi and Jennifer Neville},
   title={Modeling the Evolution of Discussion Topics and Communication to Improve Relational Classification},
   booktitle={SIGKDD SOMA},
   year={2010},
   pages={89-97},
}
Conference

, , Axel E. Bernal.

AINAW, Volume 1, Pages 745-751, .

Presented in the US, Russia, Japan, Thailand and Canada at various conferences and keynotes.

In 1957 Crick hypothesized that the genetic code was a comma free code. This property would imply the existence of a universal coding frame (More...)
@inproceedings{rossi2007crick,
   author={Jean-Louis Lassez and Ryan A. Rossi and Axel E. Bernal},
   title={Cricks Hypothesis Revisited: The Existence of a Universal Coding Frame},
   booktitle={AINAW},
   volume={1},
   year={2007},
   pages={745-751},
}
Conference

, , Kumar Jeev.

New Frontiers in Applied Artificial Intelligence (IEA/AIE), Pages 199-208, .

The main algorithms at the heart of search engines have focused on ranking and classifying sites. This is appropriate when we know what we (More...)
@article{lassez2008ranking,
   author={Jean-Louis Lassez and Ryan Rossi and Kumar Jeev},
   title={Ranking Links on the Web: Search and Surf Engines},
   journal={New Frontiers in Applied Artificial Intelligence (IEA/AIE)},
   year={2008},
   pages={199-208},
   publisher={Springer},
}
Conference

, , Stephen Sheel, Srinivas Mukkamala.

Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Pages 1068-1074, .

We address the problem of selecting and extracting key features by using singular value decomposition and latent semantic analysis. As a consequence, we are (More...)
@inproceedings{lassez2008signature,
   author={Jean-Louis Lassez and Ryan Rossi and Stephen Sheel and Srinivas Mukkamala},
   title={Signature based Intrusion Detection using Latent Semantic Analysis},
   booktitle={Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN)},
   year={2008},
   pages={1068-1074},
}
Conference

John Stamey, , Daniel Boorn, .

Proceedings of the 25th annual ACM International Conference on Design of Communication (SIGDOC), Pages 155-161, .

@inproceedings{stamey2007dynamic,
   author={John Stamey and Jean-Louis Lassez and Daniel Boorn and Ryan Rossi},
   title={Client-side Dynamic Metadata in Web 2.0},
   booktitle={Proceedings of the 25th annual ACM International Conference on Design of Communication (SIGDOC)},
   year={2007},
   pages={155-161},
}
Conference

.

Computational Intelligence and Intelligent Systems, Pages 128-137, .

We use Latent Semantic Analysis as a basis to study the languages of life. Using this approach we derive techniques to discover latent relationships (More...)
@article{rossi2009latent,
   author={Ryan A. Rossi},
   title={Latent Semantic Analysis of the Languages of Life},
   journal={Computational Intelligence and Intelligent Systems},
   year={2009},
   pages={128-137},
   publisher={Springer},
}
Conference

, , Khawaja S. Shams.

IEEE Aerospace, Pages 1-11, .

The Mars Reconnaissance Orbiter's HiRISE (High Resolution Imaging Science Experiment) camera takes the largest images of the Martian surface. The image size is typically (More...)
@inproceedings{powell2010scalable,
   author={Mark W. Powell and Ryan A. Rossi and Khawaja S. Shams},
   title={A Scalable Image Processing Framework for Gigapixel Mars and Other Celestial Body Images},
   booktitle={IEEE Aerospace},
   year={2010},
   pages={1-11},
}
Conference

Khawaja S. Shams, , Tom M. Crockett, Jeffrey S. Norris, , Tom Soderstrom.

10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), Pages 606-611, .

Amazon AWS Case Study: NASA JPL’s Desert Research and Training

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (More...)
@inproceedings{shams2010polyphony,
   author={Khawaja S. Shams and Mark W. Powell and Tom M. Crockett and Jeffrey S. Norris and Ryan Rossi and Tom Soderstrom},
   title={Polyphony: A Workflow Orchestration Framework for Cloud Computing},
   booktitle={10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid)},
   year={2010},
   pages={606-611},
}
Conference

John W. Stamey, .

Proceedings of the 27th ACM International Conference on Design of Communication, Pages 233-238, .

@inproceedings{stamey2009automatically,
   author={John W. Stamey and Ryan A. Rossi},
   title={Automatically Identifying Relations in Privacy Policies},
   booktitle={Proceedings of the 27th ACM International Conference on Design of Communication},
   year={2009},
   pages={233-238},
}
Technical report

, , .

Tech. Report Purdue CS, Pages 1-10, .

The topology of a network (connectivity of autonomous systems (ASes) or routers) has significant implications on the design of protocols and applications, and on the placement of (More...)
@inproceedings{rossi2013modeling-evol,
   author={Ryan A. Rossi and Sonia Fahmy and Nilothpal Talukder},
   title={Modeling the Evolution of the Internet Topology: A Multi-Level Evaluation Framework},
   booktitle={Tech. Report Purdue CS},
   year={2013},
   pages={1-10},
}
Technical report

, , , Mostofa A. Patwary.

arXiv preprint arXiv:1302.6256, Pages 1-9, .

We propose a fast, parallel, maximum clique algorithm for large, sparse graphs that is designed to exploit characteristics of social and information networks. We observe roughly linear (More...)
@article{rossi2013parallel-cliques,
   author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin and Mostofa A. Patwary},
   title={A Fast Parallel Maximum Clique Algorithm for Large Sparse Graphs and Temporal Strong Components},
   journal={arXiv preprint arXiv:1302.6256},
   year={2013},
   pages={1-9},
}
Technical report

, , , Mostofa A. Patwary.

arXiv preprint arXiv:1210.5802, Pages 1-11, .

Exact maximum clique finders have progressed to the point where we can investigate cliques in million-node social and information networks, as well as find strongly connected components (More...)
@article{rossi2012fastclique,
   author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin and Mostofa A. Patwary},
   title={What if CLIQUE were fast? Maximum Cliques in Information Networks and Strong Components in Temporal Networks},
   journal={arXiv preprint arXiv:1210.5802},
   year={2012},
   pages={1-11},
}
Technical report

, , , Keith Henderson.

DOE Scientific and Technical Information, LLNL-TR-514271, Pages 1-10, .

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model (More...)
@inproceedings{rossi2011modeling,
   author={Ryan A. Rossi and Brian Gallagher and Jennifer Neville and Keith Henderson},
   title={Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model},
   booktitle={DOE Scientific and Technical Information, LLNL-TR-514271},
   year={2011},
   pages={1-10},
   publisher={DOE},
}
Technical report

.

JPL Tech. Report, Pages 1-9, .

This paper proposes a new direction in Adversarial Information Retrieval through automatically ranking links. We use techniques based on Latent Semantic Analysis to define (More...)
@inproceedings{rossi2009discovering,
   author={Ryan A. Rossi},
   title={Discovering Latent Graphs with Positive and Negative Links to Eliminate Spam},
   booktitle={JPL Tech. Report},
   year={2009},
   pages={1-9},
}

.

Purdue University, Pages 163, .

Ph.D. Dissertation, Purdue University

Networks encode dependencies between entities (people, computers, proteins) and allow us to study phenomena across social, technological, and biological domains. These networks naturally evolve (More...)
@phdthesis{rossi2015purdue,
   author={Ryan A. Rossi},
   title={Improving Relational Machine Learning by Modeling Temporal Dependencies},
   school={Purdue University},
   year={2015},
   pages={163},
   publisher={ProQuest},
}
Patent

Fast and Accurate Unbiased Graphlet Estimation

, .

Patent, .

Patent application filed, USPTO App. #15/179724

@misc{rossi16patent-graphlet-estimation,
   author={Ryan A. Rossi and Rong Zhou},
   title={Fast and Accurate Unbiased Graphlet Estimation},
   booktitle={Patent},
   year={2016},
   yearfiled={2015},
}
Patent

Efficient Parallel Hybrid CPU-GPU Graph Mining and Learning via Induced Subgraph Features

, .

Patent, .

Patent application filed

@misc{rossi15patent-hybrid-cpu-gpu-graphlets,
   author={Ryan A. Rossi and Rong Zhou},
   title={Efficient Parallel Hybrid CPU-GPU Graph Mining and Learning via Induced Subgraph Features},
   booktitle={Patent},
   year={2016},
   yearfiled={2016},
}
Patent

System And Method For Compressing Graphs Via Cliques

, .

Patent, .

Patent application filed, USPTO App. #15/183561

@misc{rossi15patent-clique-compression,
   author={Ryan A. Rossi and Rong Zhou},
   title={System And Method For Compressing Graphs Via Cliques},
   booktitle={Patent},
   year={2016},
   yearfiled={2015},
}
Patent

Localized Visual Graph Filters for Complex Graph Queries

, .

Patent, .

Patent application filed, USPTO App. #15/175751

@misc{rossi16patent-localized-visual,
   author={Ryan A. Rossi and Rong Zhou},
   title={Localized Visual Graph Filters for Complex Graph Queries},
   booktitle={Patent},
   year={2016},
   yearfiled={2015},
}
Patent

Computer-implemented System And Method For Relational Time Series Learning

, .

Patent, .

Patent application filed, USPTO App. #14/955965

@misc{rossi16patent-rel-time-series,
   author={Ryan A. Rossi and Rong Zhou},
   title={Computer-implemented System And Method For Relational Time Series Learning},
   booktitle={Patent},
   year={2016},
   yearfiled={2014},
}
Patent

, .

Patent, .

Patent application filed, USPTO App. #14/325429

A system and a method perform matrix factorization. According to the system and the method, at least one matrix is received. The at least (More...)
@misc{rossi16patent-pcmf,
   author={Ryan A. Rossi and Rong Zhou},
   title={Parallel Collective Matrix Factorization Framework for Big Data},
   booktitle={Patent},
   year={2015},
   yearfiled={2014},
}
Book

, , Stephen Sheel.

Book ISBN 1329925912, .

Bioinformatics is the application of computational techniques and tools to analyze and manage biological data. This book provides an introduction to bioinformatics through the (More...)
@article{introBINF,
   author={Jean-Louis Lassez and Ryan A. Rossi and Stephen Sheel},
   title={Introduction to Bioinformatics Using Action Labs},
   journal={Book ISBN 1329925912},
   year={2009},
}

Keywords