Optimization
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Two
Neural Information Processing Systems
We show that the proposed algorithms converge to the (regularized) global optimal solution, andmoreover,theirratesofconvergence areofpolynomial orderinthe online setting and exponential order inthe finite sample setting, respectively.
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Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression
Deeksha Adil, Richard Peng, Sushant Sachdeva
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Neural Information Processing Systems http://nips.cc/
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LandscapeSurrogate: LearningDecisionLossesfor MathematicalOptimizationUnderPartialInformation
Neural Information Processing Systems
Mathematical optimization problems invarious settings havebeen widely studied, and numerous methods exist to solvethem [25,32].
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