DisCo-DSO: Joint Optimization in Hybrid Discrete-Continuous Spaces
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In this blog post, we introduce DisCo-DSO (Discrete-Continuous Deep Symbolic Optimization), a novel approach for joint optimization in hybrid discrete-continuous spaces. DisCo-DSO leverages autoregressive models and deep reinforcement learning to optimize discrete tokens and continuous parameters simultaneously. This unified approach leads to more efficient optimization, robustness to non-differentiable objectives, and superior performance in tasks like decision tree learning and symbolic regression. Let’s dive into the key innovations, applications, and results of DisCo-DSO.