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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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2 results for “SPIDER-SFO”

D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problemscs.LG

D-SPIDER-SFO solves nonconvex optimization problems faster on decentralized networks.

problem Finding a decentralized algorithm with similar convergence rate to SPIDER-SFO.

method Proposed D-SPIDER-SFO, a decentralized variant of SPIDER-SFO.

result Achieves a similar gradient computation cost to centralized SPIDER-SFO.

decentralized optimization nonconvex problems SPIDER-SFO convergence rate decentralized networks

2019-11-28abs ↗pdf ↗

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimatormath.OC

In this paper, we propose a new technique named \textit{Stochastic Path-Integrated Differential EstimatoR} (SPIDER), which can be used to track many deterministic quantities of interest with significantly reduced computational cost. We apply SPIDER to two tasks, namely the stochastic first-order and zeroth-order method…

2018-07-04abs ↗pdf ↗