Applied Optimization: Distance Geometry, Large-Scale Kernel Methods, and Algorithm Unrolling for Signal Processing
1 faculty research Applied Optimization: Distance Geometry, Large-Scale Kernel Methods, and Algorithm Unrolling for Signal Processing on GradNova.
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Applied Optimization: Distance Geometry, Large-Scale Kernel Methods, and Algorithm Unrolling for Signal Processing
High-Dimensional Data Analysis: Matrix Completion, Compressive Sensing, and Structured Sparse Recovery
Mathematical Foundations of Ai: Interpretable Machine Learning, Dictionary Learning, and Geometry-Aware Representations
Sparse and Compressive Sensing Techniques
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