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Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach.

, , and . IEEE Trans. Signal Process., (2022)

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Is There Any Recovery Guarantee with Coupled Structured Matrix Factorization for Hyperspectral Super-Resolution?, , and . CAMSAP, page 480-484. IEEE, (2019)Federated Edge Network Utility Maximization for a Multi-Server System: Algorithm and Convergence., , , and . IEEE/ACM Trans. Netw., 30 (5): 2002-2017 (2022)Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models., , , , , and . CoRR, (2020)Memory-Efficient Convex Optimization for Self-Dictionary Nonnegative Matrix Factorization., , and . IEEECONF, page 1372-1376. IEEE, (2022)Stochastic Ml Estimation for Hyperspectral Unmixing Under Endmember Variability and Nonlinear Models., , and . ICASSP, page 5315-5319. IEEE, (2020)Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation., , , and . CoRR, (2019)The IMC-PID controller design for TITO process using closed-loop identification method., , and . ICARCV, page 1339-1344. IEEE, (2014)Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation., , , and . IEEE Trans. Geosci. Remote. Sens., 58 (10): 7125-7140 (2020)A Simple Scheme for Coupled Factorization for Hyperspectral Super-Resolution: Exploiting Sparsity in an Easy Way., , , and . ICASSP, page 1-5. IEEE, (2023)Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach., , and . IEEE Trans. Signal Process., (2022)