8 citations · 21 across the 14 of their papers we have counts for
10 papers · 1 filter
Evolution With Purpose: Hierarchy-Informed Optimization of Whole-Brain Models
Hormoz Shahrzad, Niharika Gajawelli, Kaitlin Maile +2
Evolutionary search is well suited for large-scale biophysical brain modeling, where many parameters with nonlinear interactions and no tractable gradients need to be optimized. St…
GPU-Accelerated Rule Evaluation and Evolution
Hormoz Shahrzad, Risto Miikkulainen
This paper introduces an innovative approach to boost the efficiency and scalability of Evolutionary Rule-based machine Learning (ERL), a key technique in explainable AI. While tra…
Asynchronous Evolution of Deep Neural Network Architectures
Jason Liang, Hormoz Shahrzad, Risto Miikkulainen
Many evolutionary algorithms (EAs) take advantage of parallel evaluation of candidates. However, if evaluation times vary significantly, many worker nodes (i.e.,\ compute clients)…
Accelerating Evolution Through Gene Masking and Distributed Search
Hormoz Shahrzad, Risto Miikkulainen
In building practical applications of evolutionary computation (EC), two optimizations are essential. First, the parameters of the search method need to be tuned to the domain in o…
DIAS: A Domain-Independent Alife-Based Problem-Solving System
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen
A domain-independent problem-solving system based on principles of Artificial Life is introduced. In this system, DIAS, the input and output dimensions of the domain are laid out i…
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription
Olivier Francon, Santiago Gonzalez, Babak Hodjat +4
There is now significant historical data available on decision making in organizations, consisting of the decision problem, what decisions were made, and how desirable the outcomes…
Regularized Evolutionary Population-Based Training
Jason Liang, Santiago Gonzalez, Hormoz Shahrzad +1
Metalearning of deep neural network (DNN) architectures and hyperparameters has become an increasingly important area of research. At the same time, network regularization has been…
Enhanced Optimization with Composite Objectives and Novelty Pulsation
Hormoz Shahrzad, Babak Hodjat, Camille Dollé +5
An important benefit of multi-objective search is that it maintains a diverse population of candidates, which helps in deceptive problems in particular. Not all diversity is useful…
Enhanced Optimization with Composite Objectives and Novelty Selection
Hormoz Shahrzad, Daniel Fink, Risto Miikkulainen
An important benefit of multi-objective search is that it maintains a diverse population of candidates, which helps in deceptive problems in particular. Not all diversity is useful…
Evolving Deep Neural Networks
Risto Miikkulainen, Jason Liang, Elliot Meyerson +8
The success of deep learning depends on finding an architecture to fit the task. As deep learning has scaled up to more challenging tasks, the architectures have become difficult t…