OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality | ScienceToStartup | ScienceToStartup

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References (27)

[1]

Convergence of Muon with Newton-Schulz

2026Gyu-Yeol Kim, Min-hwan Oh

[2]

MARS: Unleashing the Power of Variance Reduction for Training Large Models

2024Huizhuo Yuan, Yifeng Liu et al.

[3]

Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions

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"OptEMA introduces a novel adaptive exponential moving average for stochastic optimization, improving convergence rates without requiring Lipschitz constants."

Optimization Algorithms•Score: 2•View PDF ↗

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OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality

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References (27)

Founder's Pitch

"OptEMA introduces a novel adaptive exponential moving average for stochastic optimization, improving convergence rates without requiring Lipschitz constants."

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OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality

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References (27)

Founder's Pitch

"OptEMA introduces a novel adaptive exponential moving average for stochastic optimization, improving convergence rates without requiring Lipschitz constants."

Commercial Viability Breakdown

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