3 papers
cs.LG2026
FairTabGen: High-Fidelity and Fair Synthetic Health Data Generation from Limited Samples
Nitish Nagesh, Salar Shakibhamedan, Mahdi Bagheri +4
Synthetic healthcare data generation offers a promising solution to research limitations in clinical settings caused by privacy and regulatory constraints. However, current synthet…
cs.ET2024
IMPLY-based Approximate Full Adders for Efficient Arithmetic Operations in Image Processing and Machine Learning
Melanie Qiu, Caoyueshan Fan, Gulafshan +3
To overcome the performance limitations in modern computing, such as the power wall, emerging computing paradigms are gaining increasing importance. Approximate computing offers a…
cs.AR2024
OPTIMA: Design-Space Exploration of Discharge-Based In-SRAM Computing: Quantifying Energy-Accuracy Trade-Offs
Saeed Seyedfaraji, Severin Jager, Salar Shakibhamedan +2
In-SRAM computing promises energy efficiency, but circuit nonlinearities and PVT variations pose major challenges in designing robust accelerators. To address this, we introduce OP…