A Hybrid Approach for Tracking Individual Players in Broadcast Match Videos. - Roberto L. Castro; Diego Andrade; Basilio B. Fraguela (CoRR, 2020)

Reusing Trained Layers of Convolutional Neural Networks to Shorten Hyperparameters Tuning Time. - Roberto L. Castro; Diego Andrade; Basilio B. Fraguela (CoRR, 2020)

Probing the Efficacy of Hardware-Aware Weight Pruning to Optimize the SpMM Routine on Ampere GPUs. - Roberto L. Castro; Diego Andrade; Basilio B. Fraguela (PACT, 2022)

VENOM: A Vectorized N: M Format for Unleashing the Power of Sparse Tensor Cores. - Roberto L. Castro; Andrei Ivanov; Diego Andrade; Tal Ben-Nun; Basilio B. Fraguela; Torsten Hoefler (SC, 2023)

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning. - Roberto L. Castro; Diego Andrade; Basilio B. Fraguela (IEEE Access, 2024)

MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models. - Elias Frantar; Roberto L. Castro; Jiale Chen 004; Torsten Hoefler; Dan Alistarh (Zenodo, 2024)

Adapt-S: Effective DNN Pruning via Unified Accuracy and Performance Tuning. - Roberto L. Castro; Diego Andrade; Basilio B. Fraguela (IPDPS, 2025)

MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models. - Elias Frantar; Roberto L. Castro; Jiale Chen 004; Torsten Hoefler; Dan Alistarh (PPoPP, 2025)

HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs. - Saleh Ashkboos; Mahdi Nikdan; Soroush Tabesh; Roberto L. Castro; Torsten Hoefler; Dan Alistarh (CoRR, 2025)

QuEST: Stable Training of LLMs with 1-Bit Weights and Activations. - Andrei Panferov; Jiale Chen 004; Soroush Tabesh; Roberto L. Castro; Mahdi Nikdan; Dan Alistarh (CoRR, 2025)

Quartet: Native FP4 Training Can Be Optimal for Large Language Models. - Roberto L. Castro; Andrei Panferov; Soroush Tabesh; Oliver Sieberling; Jiale Chen 004; Mahdi Nikdan; Saleh Ashkboos; Dan Alistarh (CoRR, 2025)