interpretable machine learning

Interpretable SHAP-bounded Bayesian Optimization for Underwater Acoustic Metamaterial Coating Design

  • Elnaz Hajizadeh
    • Categories Civil and Environmental Engineering, Mechanical Engineering Tags , , , ,

    We developed an interpretability informed Bayesian optimization framework to optimize underwater acoustic coatings based on polyurethane elastomers with embedded metamaterial features. A data driven model was employed to analyze the relationship between acoustic performance, specifically sound absorption and the corresponding design variables. By leveraging SHapley Additive exPlanations (SHAP), a machine learning interpretability tool, we identified … Read more

    Constrained Bayesian Accelerated Design of Acoustic Polyurethane Coatings with Metamaterial Features Under Hydrostatic Pressure

  • Elnaz Hajizadeh
    • Categories Civil and Environmental Engineering, Mechanical Engineering Tags , , ,

    Here we propose a novel, fully automated framework for accelerated design of underwater acoustic coatings, targeting the reduction of acoustic signature of naval platforms under operational conditions, by coupling Bayesian Optimization (BO) with a 2-step Finite Element Model (FEM). The developed FEMs evaluate the acoustic performance of polyurethane (PU) coatings with embedded metamaterial features under … Read more

    Mixed-Integer Optimization for Responsible Machine Learning

  • Nathan Justin
  • Qingshi Sun
  • Andrés Gómez
  • Phebe Vayanos
    • Categories Applications - OR and Management Sciences, Integer Programming, Optimization in Data Science Tags , , , , , ,

    In the last few decades, Machine Learning (ML) has achieved significant success across domains ranging from healthcare, sustainability, and the social sciences, to criminal justice and finance. But its deployment in increasingly sophisticated, critical, and sensitive areas affecting individuals, the groups they belong to, and society as a whole raises critical concerns around fairness, transparency, … Read more

    What Works Best When? A Systematic Evaluation of Heuristics for Max-Cut and QUBO

  • Iain Dunning
  • Swati Gupta
  • John Silberholz
    • Categories Meta Heuristics, Optimization Software Benchmark Tags , , , , , , ,

    Though empirical testing is broadly used to evaluate heuristics, there are shortcomings with how it is often applied in practice. In a systematic review of Max-Cut and Quadratic Unconstrained Binary Optimization (QUBO) heuristics papers, we found only 4% publish source code, only 14% compare heuristics with identical termination criteria, and most experiments are performed with … Read more