graph sparsification

Breaking the $n^1.5$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition ICML 2025 Empirical Error Estimates for Graph Sparsification AISTATS 2025 Graph Sparsification via Mixture of Graphs ICLR 2025 A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation IJCAI 2024 Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract) COLT 2024 Robust Offline Active Learning on Graphs NeurIPS 2024 Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN ICLR 2024 Why the Metric Backbone Preserves Community Structure NeurIPS 2024 Augmented Sparsifiers for Generalized Hypergraph Cuts JMLR 2023 Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks ICLR 2023 Rethinking Graph Lottery Tickets: Graph Sparsity Matters ICLR 2023 Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective ICLR 2023 Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets AAAI 2022 Principle of relevant information for graph sparsification UAI 2022 A Unified Lottery Ticket Hypothesis for Graph Neural Networks ICML 2021 Spectral vertex sparsifiers and pair-wise spanners over distributed graphs ICML 2021 Taskography: Evaluating robot task planning over large 3D scene graphs CoRL 2021 Nearly Linear Row Sampling Algorithm for Quantile Regression ICML 2020 Robust Graph Representation Learning via Neural Sparsification ICML 2020 A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening NeurIPS 2019 Graph Reduction with Spectral and Cut Guarantees JMLR 2019 Improved Dynamic Graph Learning through Fault-Tolerant Sparsification ICML 2019 On Differentially Private Graph Sparsification and Applications NeurIPS 2019 Nonlinear Graph Sparsification for SLAM RSS 2014 See the Tree Through the Lines: The Shazoo Algorithm NeurIPS 2011