Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation

28 February 2023

Papers citing "Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation"

6 / 6 papers shown

Title
$Simple Semi-supervised Knowledge Distillation from Vision-Language Models via $\mathbf{\texttt{D}}$ual-$\mathbf{\texttt{H}}$ead $\mathbf{\texttt{O}}$ptimization$ Simple Semi-supervised Knowledge Distillation from Vision-Language Models via $\mathbf{\texttt{D}}$ ual- $\mathbf{\texttt{H}}$ ead $\mathbf{\texttt{O}}$ ptimization Seongjae Kang Dong Bok Lee Hyungjoon Jang Sung Ju Hwang VLM 43 0 0 12 May 2025
Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization Zichen Miao Zhengyuan Yang Kevin Lin Ze Wang Zicheng Liu Lijuan Wang Qiang Qiu 40 3 0 04 Oct 2024
Sampling to Distill: Knowledge Transfer from Open-World Data Yuzheng Wang Zhaoyu Chen Jie M. Zhang Dingkang Yang Zuhao Ge Yang Liu Siao Liu Yunquan Sun Wenqiang Zhang Lizhe Qi 26 9 0 31 Jul 2023
Gradient Matching for Domain Generalization Yuge Shi Jeffrey S. Seely Philip H. S. Torr Siddharth Narayanaswamy Awni Y. Hannun Nicolas Usunier Gabriel Synnaeve OOD 205 246 0 20 Apr 2021
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 99 715 0 13 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 260 11,677 0 09 Mar 2017