6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
MGit: A Model Versioning and Management System
Wei Hao, Daniel Mendoza, Rafael da Silva +2
Models derived from other models are extremely common in machine learning (ML) today. For example, transfer learning is used to create task-specific models from "pre-trained" model…
cs.LO2023★ 6 cited
nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models
Matthias Cosler, Christopher Hahn, Daniel Mendoza +2
A rigorous formalization of desired system requirements is indispensable when performing any verification task. This often limits the application of verification techniques, as wri…
cs.LG2022
Dynamic Network Adaptation at Inference
Daniel Mendoza, Caroline Trippel
Machine learning (ML) inference is a real-time workload that must comply with strict Service Level Objectives (SLOs), including latency and accuracy targets. Unfortunately, ensurin…