Rutgers, The State University of New Jersey Iterative Embedding with Robust Correction using Feedback of Error Observed Praneeth Vepakomma 1 Ahmed Elgammal 2 Department of Statistics, Rutgers 1, Department of Computer Science, Rutgers 2 Electrical & Computer Engineering, FIU 1 Smart Public Safety Solutions, Motorola Solutions 1
Optional Presentation Title 2 Introduction Iterative Manifold Learning Interleaving Iterative Embedding & Feedback from Error Damping Effect of Outliers M-Estimation
Optional Presentation Title 3 Interleaved Approach: Manifold Learning M- Estimation At Iteration t:
Optional Presentation Title 4 Feedback Loop With Adjustment of Weights: Big Picture
Optional Presentation Title 5 Majorization Minimization: Uses a surrogate objective The surrogate bounds the original objective Exception: Touches the original objective at only one point Incremental Optimization (Monotonic Convergence)
Optional Presentation Title 6 Proposed Majorization Function: Linear Constraint:
Optional Presentation Title 7 MM Routine:
Optional Presentation Title 8 Robust Multiplicative Updates: M-Estimation with Geman Mcclure Function:
Optional Presentation Title 9 We Show Existence of Sharpest Majorizer: Implicit Positivity Constraints Majorization Function Condition:
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