Earning Extra Performance from Restrictive Feedbacks

28 April 2023

Ivor W. Tsang

Papers citing "Earning Extra Performance from Restrictive Feedbacks"

22 / 22 papers shown

Title
Model Adaptation: Unsupervised Domain Adaptation without Source Data Rui Li Qianfen Jiao Wenming Cao Hau-San Wong Si Wu OOD 210 488 0 26 Feb 2025
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 Ryan Turner David Eriksson M. McCourt J. Kiili Eero Laaksonen Zhen Xu Isabelle M Guyon BDL 52 298 0 20 Apr 2021
Set-valued classification -- overview via a unified framework Evgenii Chzhen Christophe Denis Mohamed Hebiri Titouan Lorieul 153 33 0 24 Feb 2021
Few-shot Image Generation with Elastic Weight Consolidation Yijun Li Richard Y. Zhang Jingwan Lu Eli Shechtman 3DH 84 169 0 04 Dec 2020
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach Suyun Liu Luis Nunes Vicente FaML 41 70 0 03 Aug 2020
Unsupervised Domain Adaptation in the Absence of Source Data Roshni Sahoo Divya Shanmugam John Guttag OOD 56 18 0 20 Jul 2020
Improving robustness against common corruptions by covariate shift adaptation Steffen Schneider E. Rusak L. Eck Oliver Bringmann Wieland Brendel Matthias Bethge VLM 92 480 0 30 Jun 2020
Pretrained Transformers Improve Out-of-Distribution Robustness Dan Hendrycks Xiaoyuan Liu Eric Wallace Adam Dziedzic R. Krishnan D. Song OOD 179 434 0 13 Apr 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 77 286 0 24 Feb 2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation Jian Liang Dapeng Hu Jiashi Feng 95 1,241 0 20 Feb 2020
On Network Design Spaces for Visual Recognition Ilija Radosavovic Justin Johnson Saining Xie Wan-Yen Lo Piotr Dollár 72 135 0 30 May 2019
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? Nima Tajbakhsh Jae Y. Shin S. Gurudu R. T. Hurst Christopher B. Kendall Michael B. Gotway Jianming Liang 222 2,526 0 02 Jun 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 352 7,498 0 02 Dec 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 220 4,307 0 07 Oct 2016
The CMA Evolution Strategy: A Tutorial N. Hansen 64 1,372 0 04 Apr 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 392 17,453 0 17 Feb 2016
Simultaneous Deep Transfer Across Domains and Tasks Eric Tzeng Judy Hoffman Trevor Darrell Kate Saenko OOD 80 1,367 0 08 Oct 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 460 43,277 0 11 Feb 2015
Learning Transferable Features with Deep Adaptation Networks Mingsheng Long Yue Cao Jianmin Wang Michael I. Jordan OOD 217 5,196 0 10 Feb 2015
Unsupervised Domain Adaptation by Backpropagation Yaroslav Ganin Victor Lempitsky OOD 233 6,022 0 26 Sep 2014
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell VLM ObjD 178 4,949 0 06 Oct 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 351 7,934 0 13 Jun 2012