Tackling Provably Hard Representative Selection via Graph Neural
Networks

Tackling Provably Hard Representative Selection via Graph Neural Networks

20 May 2022

Seyed Mehran Kazemi

Anton Tsitsulin

Hossein Esfandiari

Deepak Ramachandran

Vahab Mirrokni

Papers citing "Tackling Provably Hard Representative Selection via Graph Neural Networks"

7 / 7 papers shown

Title
UGSL: A Unified Framework for Benchmarking Graph Structure Learning Bahare Fatemi Sami Abu-El-Haija Anton Tsitsulin Seyed Mehran Kazemi Dustin Zelle Neslihan Bulut Jonathan J. Halcrow Bryan Perozzi 46 9 0 21 Aug 2023
GraphWorld: Fake Graphs Bring Real Insights for GNNs John Palowitch Anton Tsitsulin Brandon Mayer Bryan Perozzi GNN 183 68 0 28 Feb 2022
Graph Pooling via Coarsened Graph Infomax Yunsheng Pang Yunxiang Zhao Dongsheng Li GNN 27 41 0 04 May 2021
Adaptive Sampling for Minimax Fair Classification S. Shekhar Greg Fields Mohammad Ghavamzadeh T. Javidi FaML 27 36 0 01 Mar 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training Krishnateja Killamsetty D. Sivasubramanian Ganesh Ramakrishnan A. De Rishabh K. Iyer OOD 83 184 0 27 Feb 2021
Active Learning for Graph Neural Networks via Node Feature Propagation Yuexin Wu Yichong Xu Aarti Singh Yiming Yang A. Dubrawski GNN AI4CE 46 63 0 16 Oct 2019
Contextual Stochastic Block Models Y. Deshpande Andrea Montanari Elchanan Mossel S. Sen 100 151 0 23 Jul 2018