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2020 – today
- 2024
[i9]Yue Zhang, Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
HeteroMILE: a Multi-Level Graph Representation Learning Framework for Heterogeneous Graphs. CoRR abs/2404.00816 (2024)- 2023
- [c11]Saket Gurukar
, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran, Srinivasan Parthasarathy:
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. ASONAM 2023: 245-252 - [c10]Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
FairMILE: Towards an Efficient Framework for Fair Graph Representation Learning. EAAMO 2023: 11:1-11:10 - [c9]Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
Efficient Fair Graph Representation Learning Using a Multi-level Framework. WWW (Companion Volume) 2023: 298-301 - [i8]Saket Gurukar, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran, Srinivasan Parthasarathy:
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. CoRR abs/2306.14357 (2023) - 2022
- [j4]Saket Gurukar, Bethany Boettner, Christopher R. Browning, Catherine A. Calder, Srinivasan Parthasarathy:
Leveraging network representation learning and community detection for analyzing the activity profiles of adolescents. Appl. Netw. Sci. 7(1): 27 (2022) - [j3]Yuntian He, Yue Zhang, Saket Gurukar, Srinivasan Parthasarathy:
WebMILE: Democratizing Network Representation Learning at Scale. Proc. VLDB Endow. 15(12): 3718-3721 (2022) - [j2]Saket Gurukar, Nikil Pancha, Andrew Zhai, Eric Kim, Samson Hu, Srinivasan Parthasarathy, Charles Rosenberg, Jure Leskovec:
MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest. Proc. VLDB Endow. 16(4): 781-789 (2022) - [j1]Saket Gurukar, Priyesh Vijayan, Srinivasan Parthasarathy, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel:
Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress. Trans. Mach. Learn. Res. 2022 (2022) - [c8]Sean Current, Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification. EAAMO 2022: 3:1-3:14 - [i7]Sean Current, Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
FairMod: Fair Link Prediction and Recommendation via Graph Modification. CoRR abs/2201.11596 (2022) - [i6]Saket Gurukar, Nikil Pancha, Andrew Zhai, Eric Kim, Samson Hu, Srinivasan Parthasarathy, Charles Rosenberg, Jure Leskovec:
MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest. CoRR abs/2205.10666 (2022) - [i5]Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
FairMILE: A Multi-Level Framework for Fair and Scalable Graph Representation Learning. CoRR abs/2211.09925 (2022) - 2021
- [c7]Saket Gurukar, Srinivasan Parthasarathy, Rajiv Ramnath, Catherine A. Calder, Sobhan Moosavi:
LocationTrails: a federated approach to learning location embeddings. ASONAM 2021: 377-384 - [c6]Yuntian He, Saket Gurukar, Pouya Kousha, Hari Subramoni, Dhabaleswar K. Panda, Srinivasan Parthasarathy:
DistMILE: A Distributed Multi-Level Framework for Scalable Graph Embedding. HiPC 2021: 282-291 - [c5]Jiongqian Liang, Saket Gurukar, Srinivasan Parthasarathy:
MILE: A Multi-Level Framework for Scalable Graph Embedding. ICWSM 2021: 361-372 - 2020
- [c4]Saket Gurukar, Deepak Ajwani, Sourav Dutta, Juho Lauri, Srinivasan Parthasarathy, Alessandra Sala:
Towards Quantifying the Distance between Opinions. ICWSM 2020: 229-239 - [i4]Saket Gurukar, Deepak Ajwani, Sourav Dutta, Juho Lauri, Srinivasan Parthasarathy, Alessandra Sala:
Towards Quantifying the Distance between Opinions. CoRR abs/2001.09879 (2020)
2010 – 2019
- 2019
- [c3]Saket Gurukar, Srikanta Bedathur:
Time-series as Background Data for Relating Medical Diagnoses Terms. BCB 2019: 243-252 - [i3]Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, Balaraman Ravindran, Srinivasan Parthasarathy:
Network Representation Learning: Consolidation and Renewed Bearing. CoRR abs/1905.00987 (2019) - [i2]Moniba Keymanesh, Saket Gurukar, Bethany Boettner, Christopher R. Browning, Catherine A. Calder, Srinivasan Parthasarathy:
Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods. CoRR abs/1911.06359 (2019) - 2018
- [i1]Jiongqian Liang, Saket Gurukar, Srinivasan Parthasarathy:
MILE: A Multi-Level Framework for Scalable Graph Embedding. CoRR abs/1802.09612 (2018) - 2015
- [c2]Saket Gurukar, Sayan Ranu, Balaraman Ravindran:
COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks. SIGMOD Conference 2015: 475-489 - 2014
- [c1]Saket Gurukar, Balaraman Ravindran:
Temporal analysis of telecom call graphs. COMSNETS 2014: 1-6
Coauthor Index
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