1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.IR2026★ 1 cited
Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation
Camilo Gomez, Pengyang Wang, Yanjie Fu
Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents based on their relevance or impor…
cs.LG2025
NAPER: Fault Protection for Real-Time Resource-Constrained Deep Neural Networks
Rian Adam Rajagede, Muhammad Husni Santriaji, Muhammad Arya Fikriansyah +3
Fault tolerance in Deep Neural Networks (DNNs) deployed on resource-constrained systems presents unique challenges for high-accuracy applications with strict timing requirements. M…