ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning

30 January 2023

Ximei Wang

Papers citing "ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning"

30 / 30 papers shown

Title
Can Optimization Trajectories Explain Multi-Task Transfer? David Mueller Mark Dredze Nicholas Andrews 113 1 0 26 Aug 2024
StainDiffuser: MultiTask Dual Diffusion Model for Virtual Staining Tushar Kataria Beatrice Knudsen Shireen Y. Elhabian DiffM MedIm 69 9 0 17 Mar 2024
ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning Shachar Don-Yehiya Elad Venezian Colin Raffel Noam Slonim Yoav Katz Leshem Choshen MoMe 70 53 0 02 Dec 2022
Do Current Multi-Task Optimization Methods in Deep Learning Even Help? Derrick Xin Behrooz Ghorbani Ankush Garg Orhan Firat Justin Gilmer MoMe 98 65 0 23 Sep 2022
Auto-Lambda: Disentangling Dynamic Task Relationships Shikun Liu Stephen James Andrew J. Davison Edward Johns 78 75 0 07 Feb 2022
Transferability in Deep Learning: A Survey Junguang Jiang Yang Shu Jianmin Wang Mingsheng Long OOD 79 102 0 15 Jan 2022
In Defense of the Unitary Scalarization for Deep Multi-Task Learning Vitaly Kurin Alessandro De Palma Ilya Kostrikov Shimon Whiteson M. P. Kumar 71 75 0 11 Jan 2022
Auxiliary Task Update Decomposition: The Good, The Bad and The Neutral Lucio Dery Yann N. Dauphin David Grangier MoMe 61 29 0 25 Aug 2021
MultiTask-CenterNet (MCN): Efficient and Diverse Multitask Learning using an Anchor Free Approach Falk Heuer Sven Mantowsky S. S. Bukhari Georg Schneider 55 41 0 11 Aug 2021
Revisiting the Calibration of Modern Neural Networks Matthias Minderer Josip Djolonga Rob Romijnders F. Hubis Xiaohua Zhai N. Houlsby Dustin Tran Mario Lucic UQCV 98 365 0 15 Jun 2021
RotoGrad: Gradient Homogenization in Multitask Learning Adrián Javaloy Isabel Valera 84 88 0 03 Mar 2021
Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models Zirui Wang Yulia Tsvetkov Orhan Firat Yuan Cao 65 202 0 12 Oct 2020
A Survey on Negative Transfer Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu AAML 69 218 0 02 Sep 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn David Berthelot Chun-Liang Li Zizhao Zhang Nicholas Carlini E. D. Cubuk Alexey Kurakin Han Zhang Colin Raffel AAML 155 3,549 0 21 Jan 2020
Gradient Surgery for Multi-Task Learning Tianhe Yu Saurabh Kumar Abhishek Gupta Sergey Levine Karol Hausman Chelsea Finn 165 1,213 0 19 Jan 2020
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 159 1,691 0 06 Jun 2019
Which Tasks Should Be Learned Together in Multi-task Learning? Trevor Scott Standley Amir Zamir Dawn Chen Leonidas Guibas Jitendra Malik Silvio Savarese 95 517 0 18 May 2019
Adapting Auxiliary Losses Using Gradient Similarity Yunshu Du Wojciech M. Czarnecki Siddhant M. Jayakumar Mehrdad Farajtabar Razvan Pascanu Balaji Lakshminarayanan 75 158 0 05 Dec 2018
Characterizing and Avoiding Negative Transfer Zirui Wang Zihang Dai Barnabás Póczós J. Carbonell 85 415 0 24 Nov 2018
Taskonomy: Disentangling Task Transfer Learning Amir Zamir Alexander Sax Bokui (William) Shen Leonidas Guibas Jitendra Malik Silvio Savarese 118 1,217 0 23 Apr 2018
Importance Weighted Adversarial Nets for Partial Domain Adaptation Jing Zhang Zewei Ding W. Li P. Ogunbona 70 420 0 25 Mar 2018
Unsupervised Representation Learning by Predicting Image Rotations Spyros Gidaris Praveer Singh N. Komodakis OOD SSL DRL 252 3,289 0 21 Mar 2018
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation Liang-Chieh Chen Yukun Zhu George Papandreou Florian Schroff Hartwig Adam SSeg 430 13,121 0 07 Feb 2018
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics Alex Kendall Y. Gal R. Cipolla 3DH 272 3,122 0 19 May 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 813 11,894 0 09 Mar 2017
PathNet: Evolution Channels Gradient Descent in Super Neural Networks Chrisantha Fernando Dylan Banarse Charles Blundell Yori Zwols David R Ha Andrei A. Rusu Alexander Pritzel Daan Wierstra 61 880 0 30 Jan 2017
Temporal Ensembling for Semi-Supervised Learning S. Laine Timo Aila UQCV 181 2,554 0 07 Oct 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 314 8,114 0 13 Aug 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 332 7,980 0 23 May 2016
Qualitatively characterizing neural network optimization problems Ian Goodfellow Oriol Vinyals Andrew M. Saxe ODL 108 522 0 19 Dec 2014