Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification

18 August 2022

Papers citing "Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification"

8 / 8 papers shown

Title
Contrastive Representation Distillation via Multi-Scale Feature Decoupling Cuipeng Wang Tieyuan Chen Haipeng Wang 54 0 0 09 Feb 2025
Hardware-Aware DNN Compression for Homogeneous Edge Devices Kunlong Zhang Guiying Li Ning Lu Peng Yang K. Tang 54 0 0 28 Jan 2025
Quantifying Knowledge Distillation Using Partial Information Decomposition Pasan Dissanayake Faisal Hamman Barproda Halder Ilia Sucholutsky Qiuyi Zhang Sanghamitra Dutta 36 0 0 12 Nov 2024
Understanding the Effects of Projectors in Knowledge Distillation Yudong Chen Sen Wang Jiajun Liu Xuwei Xu Frank de Hoog Brano Kusy Zi Huang 26 0 0 26 Oct 2023
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,103 0 02 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,890 0 15 Sep 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 125 577 0 27 Feb 2015
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