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Gradient-Based Spectral Embeddings of Random Dot Product Graphs.

, , , , and . IEEE Trans. Signal Inf. Process. over Networks, (2024)

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A new framework for optimal classifier design, , , and . CoRR, (2013)An optimal multiclass classifier design., , and . ICPR, page 480-485. IEEE, (2016)Topology Constraints in Graphical Models., , and . NIPS, page 800-808. (2012)Algorithmic Advances for the Adjacency Spectral Embedding., , , , and . EUSIPCO, page 672-676. IEEE, (2022)Change Point Detection in Weighted and Directed Random Dot Product Graphs., , , and . EUSIPCO, page 1810-1814. IEEE, (2021)New approach for approximating the continuum wave function by Gaussian basis set., and . Comput. Phys. Commun., 183 (12): 2528-2534 (2012)Gradient-Based Spectral Embeddings of Random Dot Product Graphs., , , , and . IEEE Trans. Signal Inf. Process. over Networks, (2024)Tell me where you are and I tell you where you are going: Estimation of dynamic mobility graphs., , , and . SAM, page 1-5. IEEE, (2016)Re-Weighted ℓ _1 Algorithms within the Lagrange Duality Framework - Bringing Interpretability to Weights., and . IbPRIA (1), volume 11867 of Lecture Notes in Computer Science, page 148-160. Springer, (2019)Tracking the Adjacency Spectral Embedding for Streaming Graphs., , , , and . IEEECONF, page 847-851. IEEE, (2022)