3 papers
cs.AR2026
VIPER: Architecture-Aware Performance Modeling for Processing-in-Memory Design-Space Exploration
Haoran Geng, Tomas Sousa Pereira, Xiaoyang Lu +3
Processing-in-Memory (PIM) promises to reduce data movement overhead by executing computation in or near memory, but its realized application speedup remains highly design-dependen…
cs.LG2026
Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
Tomás Pereira, João Vitorino, Eva Maia +1
Despite the wide use of explainability techniques to attempt to understand the behavior of Artificial Intelligence (AI), the generated explanations may not always be reliable. An e…
cs.IR2021
u-cf2vec: Representation Learning for Personalized Algorithm Selection in Recommender Systems
Tomas Sousa-Pereira, Tiago Cunha, Carlos Soares
Collaborative Filtering (CF) has become the standard approach to solve recommendation systems (RS) problems. Collaborative Filtering algorithms try to make predictions about intere…