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Creators/Authors contains: "NS, Karthik Somayaji"

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  1. ; ; (, 2024 IEEE/ACM Design Automation Conference (DAC))
    Accepted Manuscript Full Text Available
  2. ; (, ACM Transactions on Design Automation of Electronic Systems)
    Analog circuit optimization and design presents a unique set of challenges in the IC design process. Many applications require for the designer to optimize for multiple competing objectives which poses a crucial challenge. Motivated by these practical aspects, we propose a novel method to tackle multi-objective optimization for analog circuit design in continuous action spaces. In particular, we propose to: (i) Extrapolate current techniques in Multi-Objective Reinforcement Learning (MORL) to continuous state and action spaces. (ii) Provide for a dynamically tunable trained model to query user defined preferences in multi-objective optimization in the analog circuit design context. 
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    Full Text Available