173 citations · 320 across the 25 of their papers we have counts for
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Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization
Albert S Berahas, Liyuan Cao, Krzysztof Choromanski +1
In this paper, we consider derivative free optimization problems, where the objective function is smooth but is computed with some amount of noise, the function evaluations are exp…
A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization
Albert S. Berahas, Liyuan Cao, Krzysztof Choromanski +1
In this paper, we analyze several methods for approximating gradients of noisy functions using only function values. These methods include finite differences, linear interpolation,…
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder +1
We present a new algorithm ASEBO for optimizing high-dimensional blackbox functions. ASEBO adapts to the geometry of the function and learns optimal sets of sensing directions, whi…