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Also known as: Nesterov-accelerated Adaptive Moment Estimation
An optimization algorithm that combines Adam’s adaptive moments with Nesterov momentum for potentially improved convergence.
DESCRIPTION
Nadam integrates Nesterov accelerated gradient into the Adam optimizer. It retains Adam’s adaptive first and second moment estimates while applying a lookahead momentum step. This can yield faster or smoother convergence on some problems. Hyperparameters mirror Adam (learning rate, beta1, beta2) with Nesterov adjustments. Support exists in Keras and PyTorch. As with all optimizers, performance is problem-dependent and sensitive to learning rate.
ALTERNATIVE DEFINITIONS
Keras
Nadam optimization is Adam with Nesterov momentum.
Direct, concise equivalence with Adam plus Nesterov.
arXiv
We incorporate Nesterov momentum into Adam, resulting in Nadam, which can provide better convergence properties in practice.
Emphasizes incorporation and potential convergence benefits.
RELATED TERMS
Nesterov Momentum Stochastic Gradient Descent Optimizer Learning Rate Scheduler Bias Correction Adaptive Optimization Beta Parameter Regularization
COMPETING TERMS
KNOWLEDGE AREAS
TARGET AUDIENCE
Data Scientist AI Engineer MLOps Engineer
EXTERNAL SOURCES
- Wikipedia - Stochastic gradient descent#Adam
- PyTorch - PyTorch NAdam optimizer docs
- Keras - Keras Nadam optimizer reference
TOP QUESTIONS
How does Nadam differ from Adam?
Nadam adds Nesterov momentum to Adam’s adaptive moments, using a lookahead gradient to refine the update direction.
Category: Comparison
When should I try Nadam?
Try Nadam when Adam plateaus or oscillates; the lookahead step may stabilize and accelerate training on some tasks.
Category: Decision
What hyperparameters does Nadam use?
It uses learning rate, beta1, beta2, and epsilon like Adam; defaults are often similar, but tuning may differ slightly.
Category: HowTo
Is Nadam always better than Adam?
No. Performance is problem-dependent; sometimes Adam or SGD with momentum generalizes better.
Category: Misunderstanding
Does Nadam increase computation cost?
Overhead is minimal relative to Adam; it mainly changes the update formula with a lookahead term.
Category: Performance
Is Nadam supported in major frameworks?
Yes, Keras and PyTorch provide Nadam implementations with standard interfaces.
Category: Implementation
How do learning rate schedules interact with Nadam?
Warmup and decay schedules can improve stability and final accuracy, just as with Adam.
Category: HowTo
What tasks benefit most from Nadam?
Tasks with noisy gradients or sensitive curvature may benefit from the additional lookahead stabilization.
Category: UseCases
Can I switch from Adam to Nadam mid-training?
Yes, but ensure state compatibility; resetting or carefully transferring moments may be necessary.
Category: Operations