eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
IEEE

A Universal Framework for Automatically Generating Single-and Multi-Objective Evolutionary Algorithms

Abstract: The automated design of evolutionary algorithms (EAs) is receiving more and more attention, which considerably reduces the labor-intensive process of algorithm design demanding expertise.
IEEE

Learning-Based Temporal Sequence of Constrained Handling Selection for Constrained Multi-objective Evolutionary Optimization

Abstract: Constraint-handling techniques and genetic operators are two crucial components in constrained multi-objective evolutionary algorithms (CMOEAs). Recent research in most of CMOEAs has ...
Microsoft

Rethinking Machine Learning Collective Communication as a Multi Commodity Flow problem

Cloud operators utilize collective communication optimizers to enhance the efficiency of the single-tenant, centrally managed training clusters they manage. However, current optimizers struggle to ...