63 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of Texas at AustinUS9 papers
- Cognizant (India)IN5 papers
- Google (United States)US2 papers
- American UniversityUS1 paper
- Autodesk (United States)US1 paper
- Bank IndonesiaID1 paper
- Criteo (France)FR1 paper
- Institut de Recherche en Informatique de ToulouseFR1 paper
- Institute for Exercise and Environmental MedicineUS1 paper
- Institute of Electrical and Electronics EngineersUS1 paper
- Institut Polytechnique de BordeauxFR1 paper
- Ludwig-Maximilians-Universität MünchenDE1 paper
16 papers
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…
Optimizing Chlorination in Water Distribution Systems via Surrogate-assisted Neuroevolution
Rivaaj Monsia, Daniel Young, Olivier Francon +1
Ensuring the microbiological safety of large, heterogeneous water distribution systems (WDS) typically requires managing appropriate levels of disinfectant residuals including chlo…
Push Down Optimization for Distributed Multi Cloud Data Integration
Ravi Kiran Kodali, Vinoth Punniyamoorthy, Akash Kumar Agarwal +5
Enterprises increasingly adopt multi cloud architectures to take advantage of diverse database engines, regional availability, and cost models. In these environments, ETL pipelines…
Enhancing XR Auditory Realism via Multimodal Scene-Aware Acoustic Rendering
Tianyu Xu, Jihan Li, Penghe Zu +9
In Extended Reality (XR), rendering sound that accurately simulates real-world acoustics is pivotal in creating lifelike and believable virtual experiences. However, existing XR sp…
Integration of imprint-free and low coercivity ferroelectric BaTiO3 thin films on silicon
Jingtian Zhao, Beatriz Noheda, Martin F. Sarott
Highly-crystalline ferroelectric oxides integrated on Si hold great promise for energy-efficient memory and logic technologies. Exploiting epitaxial strain engineering in these mat…
ADALog: Adaptive Unsupervised Anomaly detection in Logs with Self-attention Masked Language Model
Przemek Pospieszny, Wojciech Mormul, Karolina Szyndler +1
Modern software systems generate extensive heterogeneous log data with dynamic formats, fragmented event sequences, and varying temporal patterns, making anomaly detection both cru…
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…
Discovering Effective Policies for Land-Use Planning with Neuroevolution
Daniel Young, Olivier Francon, Elliot Meyerson +5
How areas of land are allocated for different uses, such as forests, urban areas, and agriculture, has a large effect on the terrestrial carbon balance, and therefore climate chang…
Language Model Crossover: Variation through Few-Shot Prompting
Elliot Meyerson, Mark J. Nelson, Herbie Bradley +4
This paper pursues the insight that language models naturally enable an intelligent variation operator similar in spirit to evolutionary crossover. In particular, language models o…
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…
Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings)
Elliot Meyerson, Xin Qiu, Risto Miikkulainen
This paper characterizes the inherent power of evolutionary algorithms. This power depends on the computational properties of the genetic encoding. With some encodings, two parents…
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
This paper frames a general prediction system as an observer traveling around a continuous space, measuring values at some locations, and predicting them at others. The observer is…
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel
Xin Qiu, Elliot Meyerson, Risto Miikkulainen
Neural Networks (NNs) have been extensively used for a wide spectrum of real-world regression tasks, where the goal is to predict a numerical outcome such as revenue, effectiveness…
A Comparison of the Taguchi Method and Evolutionary Optimization in Multivariate Testing
Jingbo Jiang, Diego Legrand, Robert Severn +1
Multivariate testing has recently emerged as a promising technique in web interface design. In contrast to the standard A/B testing, multivariate approach aims at evaluating a larg…
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering
Elliot Meyerson, Risto Miikkulainen
Existing deep multitask learning (MTL) approaches align layers shared between tasks in a parallel ordering. Such an organization significantly constricts the types of shared struct…
Surprising properties of dropout in deep networks
David P. Helmbold, Philip M. Long
We analyze dropout in deep networks with rectified linear units and the quadratic loss. Our results expose surprising differences between the behavior of dropout and more tradition…