K
Kyle Hundman
Researcher at California Institute of Technology
Publications - 4
Citations - 810
Kyle Hundman is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Anomaly detection & Key (cryptography). The author has an hindex of 3, co-authored 4 publications receiving 248 citations.
Papers
More filters
Proceedings ArticleDOI
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
TL;DR: The effectiveness of Long Short-Term Memory networks, a type of Recurrent Neural Network, in overcoming issues using expert-labeled telemetry anomaly data from the Soil Moisture Active Passive (SMAP) satellite and the Mars Science Laboratory (MSL) rover, Curiosity is demonstrated.
Proceedings ArticleDOI
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
TL;DR: In this article, Long Short-Term Memory (LSTM) networks, a type of Recurrent Neural Network (RNN), were used for anomaly detection in telemetry anomaly data from the Soil Moisture Active Passive (SMAP) satellite and the Mars Science Laboratory (MSL) rover, Curiosity.
Proceedings ArticleDOI
Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection
TL;DR: The findings show that, while automatic trafficking detection is an important application of AI for social good, it also provides cautionary lessons for deploying predictive machine learning algorithms without appropriate de-biasing.
Posted Content
Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection
TL;DR: In this paper, the authors define and study the problem of trafficking detection and present a trafficking detection pipeline architecture developed over three years of research within the DARPA Memex program, and conduct post hoc bias analyses and presents a bias mitigation plan.