Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks
via Aggregated Early Exits

Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits

28 January 2023

Eugenio Lomurno

Matteo Matteucci

Papers citing "Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits"

5 / 5 papers shown

Title
Conditional computation in neural networks: principles and research trends Simone Scardapane Alessandro Baiocchi Alessio Devoto V. Marsocci Pasquale Minervini Jary Pomponi 34 1 0 12 Mar 2024
Neural Architecture Transfer 2: A Paradigm for Improving Efficiency in Multi-Objective Neural Architecture Search Simone Sarti Eugenio Lomurno Matteo Matteucci 19 0 0 03 Jul 2023
Enhancing Once-For-All: A Study on Parallel Blocks, Skip Connections and Early Exits Simone Sarti Eugenio Lomurno Andrea Falanti Matteo Matteucci 23 3 0 03 Feb 2023
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 270 36,371 0 25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014