Multiobjective Optimization and Unsupervised Lexical Acquisition for Named Entity Recognition and Classification

qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson sampling

Classical evolutionary approaches for multiobjective optimization are quite accurate but incur a lot of queries to the objectives; this can be prohibitive when objectives are expensive oracles. A sample-efficient approac…

Scalarizing Functions in Bayesian Multiobjective Optimization

Scalarizing functions have been widely used to convert a multiobjective optimization problem into a single objective optimization problem. However, their use in solving (computationally) expensive multi- and many-objecti…

A framework for fully autonomous design of materials via multiobjective optimization and active learning: challenges and next steps

In order to deploy machine learning in a real-world self-driving laboratory where data acquisition is costly and there are multiple competing design criteria, systems need to be able to intelligently sample while balanci…

Wasserstein Distributionally Robust Inverse Multiobjective Optimization

Inverse multiobjective optimization provides a general framework for the unsupervised learning task of inferring parameters of a multiobjective decision making problem (DMP), based on a set of observed decisions from the…

Multi-way Tensor Factorization for Unsupervised Lexical Acquisition