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Found 6 papers, 1 papers with code
Experience-Based Evolutionary Algorithms for Expensive Optimization
Our experimental results on expensive multi-objective and constrained optimization problems demonstrate that experiences gained from related tasks are beneficial for the saving of evaluation budgets on the target problem.
Integrating features from lymph node stations for metastatic lymph node detection
The branch targets to solve a closely related task on the LN station level, i. e., classifying whether an LN station contains metastatic LN or not, so as to learn representations for LN stations.
A multi-objective optimization framework for on-line ridesharing systems
The ultimate goal of ridesharing systems is to matchtravelers who do not have a vehicle with those travelers whowant to share their vehicle.
Hot and counter-rotating star-forming disk galaxies in IllustrisTNG and their real-world counterparts
A key feature of a large population of low-mass, late-type disk galaxies are star-forming disks with exponential light distributions.
Astrophysics of Galaxies
Towards Interpretable-AI Policies Induction using Evolutionary Nonlinear Decision Trees for Discrete Action Systems
In this paper, we use a recently proposed nonlinear decision-tree (NLDT) approach to find a hierarchical set of control rules in an attempt to maximize the open-loop performance for approximating and explaining the pre-trained black-box DRL (oracle) agent using the labelled state-action dataset.
Unravelling stellar populations in the Andromeda Galaxy
The formation of the bar lead to the re-arrangement of the [Z/H] distribution, causing a flat gradient along the bar.
Astrophysics of Galaxies
