Nevergrad: An open source tool for derivative-free optimization

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Introduced and open-sourced Nevergrad, a Python library for derivative-free optimization. Nevergrad provides a standard ask-and-tell framework with a collection of gradient-free optimization algorithms (e.g., Differential evolution, Sequential quadratic programming, FastGA, Covariance matrix adaptation, Particle swarm optimization). It enables easier comparison of state-of-the-art methods for various machine learning problems, including multimodal, ill-conditioned, separable, discrete, continuous, mixed, and noisy problems. The library also includes tools for implementing and benchmarking algorithms, with specific examples for noisy and discrete optimization scenarios.