Scalable Nonconvex Optimization Algorithms: Theory and Applications
Modern statistical problems often involve minimizing objective functions that are not necessarily convex or smooth. In this study, we devote to developing scalable algorithms for nonconvex optimization with statistical guarantees. We first investigate a broad surrogate framework defined by generaliz...
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| Format: | Others |
| Language: | English English |
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Florida State University
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| Online Access: | http://purl.flvc.org/fsu/fd/2018_Su_Wang_fsu_0071E_14775 |