This is a decommissioned version of ERA which is running to enable completion of migration processes. All new collections and items and all edits to existing items should go to our new ERA instance at https://ualberta.scholaris.ca - Please contact us at erahelp@ualberta.ca for assistance!
Search
Skip to Search Results- 4Computer Science
- 1Budgeted Gradient Descent
- 1Evaluation framework
- 1Large Language Model
- 1Machine Learning
- 1Neural Networks
-
Budgeted Gradient Descent: Selective Gradient Optimization for Addressing Misclassifications in DNNs
DownloadFall 2024
Artificial neural networks have become a popular learning approach for theirability to generalize well to unseen data. However, misclassifications can still occur due to various data-related issues, such as adversarial inputs, out-of-distribution samples, and model-related challenges, such as...
-
Fall 2024
Training large language models (LLMs) often requires extensive human supervision and struggles with modeling long-range text semantic dependencies. To address these challenges, we introduce our framework ELITE — Evolving Language models Iteratively Through self-critiquE — inspired by human...
-
Fall 2023
This is a comprehensive examination of the diagnostic landscape in psychiatry and the role precision psychiatry might play in redefining how we classify illnesses. This thesis delves into three areas that currently exist in psychiatry today and is divided into five chapters. The first and second...
-
Simulation-based Sensor Configuration Optimization to Detect Human Activities in Smart Indoor Spaces
DownloadFall 2023
Smart indoor spaces include a network of interconnected sensors, predictive models, and actuators to sense occupants’ activities and act to improve living. These ubiquitous systems are increasingly popular due to their potential to improve energy efficiency, comfort, and safety in buildings....