Few-shot learning of neural networks from scratch by pseudo example
optimization

Few-shot learning of neural networks from scratch by pseudo example optimization

8 February 2018

Zoubin Ghahramani

Papers citing "Few-shot learning of neural networks from scratch by pseudo example optimization"

9 / 9 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 57 0 0 12 May 2025
Knowledge Distillation: A Survey Jianping Gou B. Yu Stephen J. Maybank Dacheng Tao VLM 19 2,843 0 09 Jun 2020
Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model Dongdong Wang Yandong Li Liqiang Wang Boqing Gong 24 48 0 31 Mar 2020
BEAN: Interpretable Representation Learning with Biologically-Enhanced Artificial Neuronal Assembly Regularization Yuyang Gao Giorgio Ascoli Liang Zhao 17 15 0 27 Sep 2019
Zero-shot Knowledge Transfer via Adversarial Belief Matching P. Micaelli Amos Storkey 17 228 0 23 May 2019
Zero-Shot Knowledge Distillation in Deep Networks Gaurav Kumar Nayak Konda Reddy Mopuri Vaisakh Shaj R. Venkatesh Babu Anirban Chakraborty 22 245 0 20 May 2019
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 68 171 0 08 Jul 2017
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 261 1,275 0 06 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015