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Centrality-constrained graph embedding., and . ICASSP, page 3113-3117. IEEE, (2013)A proximal gradient algorithm for tracking cascades over networks., , and . ICASSP, page 4778-4782. IEEE, (2014)Kernel-based embeddings for large graphs with centrality constraints., and . ICASSP, page 1901-1905. IEEE, (2015)Topology inference of directed graphs using nonlinear structural vector autoregressive models., , and . ICASSP, page 6513-6517. IEEE, (2017)Nonlinear Structural Vector Autoregressive Models With Application to Directed Brain Networks., , and . IEEE Trans. Signal Process., 67 (20): 5325-5339 (2019)Nonlinear structural equation models for network topology inference., , and . CISS, page 163-168. IEEE, (2016)Kernel-Based Structural Equation Models for Topology Identification of Directed Networks., , and . IEEE Trans. Signal Process., 65 (10): 2503-2516 (2017)Proximal-Gradient Algorithms for Tracking Cascades Over Social Networks., , and . J. Sel. Topics Signal Processing, 8 (4): 563-575 (2014)Tracking dynamic piecewise-constant network topologies via adaptive tensor factorization., , and . GlobalSIP, page 375-379. IEEE, (2016)Dynamic Structural Equation Models for Social Network Topology Inference., , and . CoRR, (2013)