Nesreen K. Ahmed

CoRR, 2024

Bias and Fairness in Large Language Models: A Survey.

[BibT_eX]

[DOI]

Comput. Linguistics, 2024

The 5th International Workshop on Machine Learning on Graphs (MLoG).

[BibT_eX]

[DOI]

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Structure-Aware Framework for Learning Device Placements on Computation Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

GrAPL 2024 Preface and Committees.

[BibT_eX]

[DOI]

Manoj Kumar

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

Editing Partially Observable Networks via Graph Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Forward Learning of Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks.

[BibT_eX]

[DOI]

Proceedings of the IEEE High Performance Extreme Computing Conference, 2024

OMPGPT: A Generative Pre-trained Transformer Model for OpenMP.

[BibT_eX]

[DOI]

Proceedings of the Euro-Par 2024: Parallel Processing, 2024

Structure Guided Prompt: Instructing Large Language Model in Multi-Step Reasoning by Exploring Graph Structure of the Text.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks.

[BibT_eX]

[DOI]

CoRR, 2023

Leveraging Reinforcement Learning and Large Language Models for Code Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Leveraging Graph Diffusion Models for Network Refinement Tasks.

[BibT_eX]

[DOI]

CoRR, 2023

CompCodeVet: A Compiler-guided Validation and Enhancement Approach for Code Dataset.

[BibT_eX]

[DOI]

CoRR, 2023

AUTOPARLLM: GNN-Guided Automatic Code Parallelization using Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Scope is all you need: Transforming LLMs for HPC Code.

[BibT_eX]

[DOI]

CoRR, 2023

On Graph Time-Series Representations for Temporal Networks.

[BibT_eX]

[DOI]

Namyong Park

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

A ML-based Approach for HTML-based Style Recommendation.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis.

[BibT_eX]

[DOI]

Ali TehraniJamsaz

Le Chen

Ali Jannesari

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation.

[BibT_eX]

[DOI]

Le Chen

Hung Phan

Ali Jannesari

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Augmenting Recurrent Graph Neural Networks with a Cache.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Neural Compositional Rule Learning for Knowledge Graph Reasoning.

[BibT_eX]

[DOI]

Kewei Cheng

Yizhou Sun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Estimation of Local Causal Effects in Graphs via Neighborhood Pooling.

[BibT_eX]

[DOI]

Somdeb Sarkhel

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Personalized Visualization Recommendation.

[BibT_eX]

[DOI]

ACM Trans. Web, 2022

Role-Based Graph Embeddings.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2022

A Hypergraph Neural Network Framework for Learning Hyperedge-Dependent Node Embeddings.

[BibT_eX]

[DOI]

CoRR, 2022

Graph Learning with Localized Neighborhood Fairness.

[BibT_eX]

[DOI]

CoRR, 2022

Memory-Augmented Graph Neural Networks: A Neuroscience Perspective.

[BibT_eX]

[DOI]

CoRR, 2022

AutoGML: Fast Automatic Model Selection for Graph Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2022

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2022

CGC: Contrastive Graph Clustering for Community Detection and Tracking.

[BibT_eX]

[DOI]

Namyong Park

Iftikhar Ahamath Burhanuddin

CoRR, 2022

CGC: Contrastive Graph Clustering forCommunity Detection and Tracking.

[BibT_eX]

[DOI]

Namyong Park

Iftikhar Ahamath Burhanuddin

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Technology Growth Ranking Using Temporal Graph Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach.

[BibT_eX]

[DOI]

Ancy Sarah Tom

George Karypis

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Network Report: A Structured Description for Network Datasets.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Heterogeneous Graphlets.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2021

Online Sampling of Temporal Networks.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2021

Dynamic Node Embeddings From Edge Streams.

[BibT_eX]

[DOI]

IEEE Trans. Emerg. Top. Comput. Intell., 2021

Deep graph similarity learning: a survey.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2021

Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes.

[BibT_eX]

[DOI]

CoRR, 2021

DistGNN: scalable distributed training for large-scale graph neural networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2021

A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems.

[BibT_eX]

[DOI]

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

From Closing Triangles to Higher-Order Motif Closures for Better Unsupervised Online Link Prediction.

[BibT_eX]

[DOI]

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Learning Code Representations Using Multifractal-based Graph Networks.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Graph Neural Networks with Heterophily.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Deep Inductive Graph Representation Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2020

On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2020

Correction to: Complex networks are structurally distinguishable by domain.

[BibT_eX]

[DOI]

Soc. Netw. Anal. Min., 2020

PIUMA: Programmable Integrated Unified Memory Architecture.

[BibT_eX]

[DOI]

CoRR, 2020

A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems.

[BibT_eX]

[DOI]

CoRR, 2020

Inferring Individual Level Causal Models from Graph-based Relational Time Series.

[BibT_eX]

[DOI]

Somdeb Sarkhel

CoRR, 2020

Fast and Accurate Estimation of Typed Graphlets.

[BibT_eX]

[DOI]

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

From Closing Triangles to Closing Higher-Order Motifs.

[BibT_eX]

[DOI]

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Fast Hierarchical Graph Clustering in Linear-Time.

[BibT_eX]

[DOI]

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

A Structural Graph Representation Learning Framework.

[BibT_eX]

[DOI]

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions.

[BibT_eX]

[DOI]

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Adaptive Shrinkage Estimation for Streaming Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

NeuroVectorizer: end-to-end vectorization with deep reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

2019

Estimation of Graphlet Counts in Massive Networks.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2019

Attention Models in Graphs: A Survey.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2019

Complex networks are structurally distinguishable by domain.

[BibT_eX]

[DOI]

Soc. Netw. Anal. Min., 2019

Temporal Network Sampling.

[BibT_eX]

[DOI]

CoRR, 2019

From Community to Role-based Graph Embeddings.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Reinforcement Learning in System Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Network Shrinkage Estimation.

[BibT_eX]

[DOI]

CoRR, 2019

Linear-time Hierarchical Community Detection.

[BibT_eX]

[DOI]

CoRR, 2019

Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs.

[BibT_eX]

[DOI]

CoRR, 2019

Temporal Network Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Heterogeneous Network Motifs.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Graph Similarity Learning for Brain Data Analysis.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Philip S. Yu

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Interactive Visual Graph Mining and Learning.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2018

Similarity Learning with Higher-Order Proximity for Brain Network Analysis.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Philip S. Yu

CoRR, 2018

Learning Role-based Graph Embeddings.

[BibT_eX]

[DOI]

CoRR, 2018

HONE: Higher-Order Network Embeddings.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Inductive Network Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Higher-order Network Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Continuous-Time Dynamic Network Embeddings.

[BibT_eX]

[DOI]

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

GraML 2018 Keynote.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, 2018

Similarity-based Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Sampling for Approximate Bipartite Network Projection.

[BibT_eX]

[DOI]

Nick G. Duffield

Liangzhen Xia

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Interactive Higher-Order Network Analysis.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Relational Similarity Machines (RSM): A Similarity-based Learning Framework for Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Dynamic Network Embeddings: From Random Walks to Temporal Random Walks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

On Sampling from Massive Graph Streams.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2017

Graphlet decomposition: framework, algorithms, and applications.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2017

Estimating Node Similarity by Sampling Streaming Bipartite Graphs.

[BibT_eX]

[DOI]

Nick G. Duffield

Liangzhen Xia

CoRR, 2017

Representation Learning in Large Attributed Graphs.

[BibT_eX]

[DOI]

CoRR, 2017

A Framework for Generalizing Graph-based Representation Learning Methods.

[BibT_eX]

[DOI]

CoRR, 2017

Network Classification and Categorization.

[BibT_eX]

[DOI]

James P. Canning

Emma E. Ingram

Sammantha Nowak-Wolff

Adriana M. Ortiz

Karl Robert Bruce Schmitt

Sucheta Soundarajan

CoRR, 2017

Deep Feature Learning for Graphs.

[BibT_eX]

[DOI]

CoRR, 2017

Estimation of Graphlet Statistics.

[BibT_eX]

[DOI]

CoRR, 2017

Edge Role Discovery via Higher-Order Structures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Exploring optimizations on shared-memory platforms for parallel triangle counting algorithms.

[BibT_eX]

[DOI]

Midhunchandra Kodiyath

Ibrahim Hur

Fabrizio Petrini

George Karypis

Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

Truss decomposition on shared-memory parallel systems.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

A Formal Approach to Modeling the Cost of Cognitive Control.

[BibT_eX]

[DOI]

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Stream Aggregation Through Order Sampling.

[BibT_eX]

[DOI]

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

E-CLoG: Counting edge-centric local graphlets.

[BibT_eX]

[DOI]

Vachik S. Dave

Mohammad Al Hasan

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

A Higher-Order Latent Space Network Model.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Relational Similarity Machines.

[BibT_eX]

[DOI]

CoRR, 2016

Revisiting Role Discovery in Networks: From Node to Edge Roles.

[BibT_eX]

[DOI]

CoRR, 2016

Exact and Estimation of Local Edge-centric Graphlet Counts.

[BibT_eX]

[DOI]

Theodore L. Willke

Proceedings of the 5th International Workshop on Big Data, 2016

Estimation of local subgraph counts.

[BibT_eX]

[DOI]

Theodore L. Willke

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery

[BibT_eX]

[DOI]

Nesreen Kamel Ahmed

PhD thesis, 2015

Role Discovery in Networks.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2015

An Interactive Data Repository with Visual Analytics.

[BibT_eX]

[DOI]

SIGKDD Explor., 2015

A Web-based Interactive Visual Graph Analytics Platform.

[BibT_eX]

[DOI]

CoRR, 2015

Fast Parallel Graphlet Counting for Large Networks.

[BibT_eX]

[DOI]

CoRR, 2015

Interactive Visual Graph Analytics on the Web.

[BibT_eX]

[DOI]

Nesreen Kamel Ahmed

Ryan Anthony Rossi

Proceedings of the Ninth International Conference on Web and Social Media, 2015

Efficient Graphlet Counting for Large Networks.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

The Network Data Repository with Interactive Graph Analytics and Visualization.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Coloring large complex networks.

[BibT_eX]

[DOI]

Soc. Netw. Anal. Min., 2014

NetworkRepository: A Graph Data Repository with Visual Interactive Analytics.

[BibT_eX]

[DOI]

CoRR, 2014

Learning the Latent State Space of Time-Varying Graphs.

[BibT_eX]

[DOI]

Christopher Cole

CoRR, 2014

Graph sample and hold: a framework for big-graph analytics.

[BibT_eX]

[DOI]

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Network Sampling: From Static to Streaming Graphs.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2013

2012

Does a Daily Deal Promotion Signal a Distressed Business? An Empirical Investigation of Small Business Survival

[BibT_eX]

[DOI]

Ayman Farahat

Utpal M. Dholakia

CoRR, 2012

Space-efficient sampling from social activity streams.

[BibT_eX]

[DOI]

Proceedings of the 1st International Workshop on Big Data, 2012

Network Sampling Designs for Relational Classification.

[BibT_eX]

[DOI]

Proceedings of the Sixth International Conference on Weblogs and Social Media, 2012

2010

Time-based sampling of social network activity graphs.

[BibT_eX]

[DOI]

Fredrick J. Berchmans