8 citations · 8 across the 5 of their papers we have counts for
5 papers
Scout: Open-World Species Recognition on the Edge
Mohammad Mehdi Rastikerdar, Hui Guan, Deepak Ganesan
Large vision-language models (VLMs) enable recognition beyond a fixed class set, but their computational demands prevent them from running on many edge devices. Cloud offload makes…
Kalypso: Relational LLM Serving
Hojae Son, Md Ashraful Islam, Huy Gia Cao +2
Large language models are increasingly used as semantic operators for filtering, extracting, ranking, joining, and transforming unstructured data. Existing semantic query processin…
WildFit: Autonomous In-situ Model Adaptation for Resource-Constrained IoT Systems
Mohammad Mehdi Rastikerdar, Jin Huang, Hui Guan +1
Resource-constrained IoT devices increasingly rely on deep learning models, however, these models experience significant accuracy drops due to domain shifts when encountering varia…
Loki: A System for Serving ML Inference Pipelines with Hardware and Accuracy Scaling
Sohaib Ahmad, Hui Guan, Ramesh K. Sitaraman
The rapid adoption of machine learning (ML) has underscored the importance of serving ML models with high throughput and resource efficiency. Traditional approaches to managing inc…
Efficient IoT Inference via Context-Awareness
Mohammad Mehdi Rastikerdar, Jin Huang, Shiwei Fang +2
While existing strategies to execute deep learning-based classification on low-power platforms assume the models are trained on all classes of interest, this paper posits that adop…