Variance reduction techniques are statistical methods used to decrease the variability of an estimator without increasing its bias. These techniques are particularly useful in simulation methods like Monte Carlo integration, where reducing variance leads to more accurate estimates and faster convergence to the true value. By applying these techniques, one can achieve more reliable results in simulations, which is crucial for decision-making in various fields.
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