A compression-driven training framework for embedded deep neural networks. - Matteo Grimaldi; Federico Pugliese; Valerio Tenace; Andrea Calimera (INTESA@ESWEEK, 2018)

Arbitrary-Precision Convolutional Neural Networks on Low-Power IoT Processors. - Valentino Peluso; Matteo Grimaldi; Andrea Calimera (VLSI-SoC, 2019)

Optimality Assessment of Memory-Bounded ConvNets Deployed on Resource-Constrained RISC Cores. - Matteo Grimaldi; Valentino Peluso; Andrea Calimera (IEEE Access, 2019)

Layer-Wise Compressive Training for Convolutional Neural Networks. - Matteo Grimaldi; Valerio Tenace; Andrea Calimera (Future Internet, 2019)

EAST: Encoding-Aware Sparse Training for Deep Memory Compression of ConvNets. - Matteo Grimaldi; Valentino Peluso; Andrea Calimera (AICAS, 2020)

Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity. - Matteo Grimaldi; Darshan C. Ganji; Ivan Lazarevich; Sudhakar Sah Deeplite (ICCV (Workshops), 2023)

YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems. - Ivan Lazarevich; Matteo Grimaldi; Ravish Kumar; Saptarshi Mitra; Shahrukh Khan; Sudhakar Sah (ICCV (Workshops), 2023)

Dynamic ConvNets on Tiny Devices via Nested Sparsity. - Matteo Grimaldi; Luca Mocerino; Antonio Cipolletta; Andrea Calimera (IEEE Internet Things J., 2023)

MCUBench: A Benchmark of Tiny Object Detectors on MCUs. - Sudhakar Sah; Darshan C. Ganji; Matteo Grimaldi; Ravish Kumar; Alexander Hoffman; Honnesh Rohmetra; Ehsan Saboori (ECCV Workshops (11), 2024)