84 citations · 227 across the 25 of their papers we have counts for
4 papers · 1 filter
Fitness Approximation through Machine Learning
Itai Tzruia, Tomer Halperin, Moshe Sipper +1
We present a novel approach to performing fitness approximation in genetic algorithms (GAs) using machine-learning (ML) models, through dynamic adaptation to the evolutionary state…
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models
Raz Lapid, Moshe Sipper
Modern image-to-text systems typically adopt the encoder-decoder framework, which comprises two main components: an image encoder, responsible for extracting image features, and a…
A Melting Pot of Evolution and Learning
Moshe Sipper, Achiya Elyasaf, Tomer Halperin +5
We survey eight recent works by our group, involving the successful blending of evolutionary algorithms with machine learning and deep learning: 1. Binary and Multinomial Classific…
Classy Ensemble: A Novel Ensemble Algorithm for Classification
Moshe Sipper
We present Classy Ensemble, a novel ensemble-generation algorithm for classification tasks, which aggregates models through a weighted combination of per-class accuracy. Tested ove…