Multi-task Machine Learning Paper List

A list of papers that are relevant to multi-task machine learning. Inspired by awesome-deep-learning-papers and awesome-adversarial-machine-learning.

Table of Contents

• Hard Parameter Sharing
• Soft Parameter Sharing
• Neural Architecture Search
• Others

Hard Parameter Sharing

• PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning.
  Arun Mallya, Svetlana Lazebnik.
  CVPR 2018.
• Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back.
  Elliot Meyerson, Risto Miikkulainen.
  ICML 2018.
• Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering.
  Elliot Meyerson, Risto Miikkulainen.
  ICLR 2018.
• Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning.
  Clemens Rosenbaum, Tim Klinger, Matthew Riemer.
  ICLR 2018.
• Unifying and Merging Well-trained Deep Neural Networks for Inference Stage.
  Yi-Min Chou, Yi-Ming Chan, Jia-Hong Lee, Chih-Yi Chiu, Chu-Song Chen.
  IJCAI-ECAI 2018.
• Multi-task Sequence to Sequence Learning.
  Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser.
  ICLR 2016.

Soft Parameter Sharing

• Cross-stitch Networks for Multi-task Learning.
  Ishan Misra, Abhinav Shrivastava, Abhinav Gupta, Martial Hebert.
  CVPR 2016.

Neural Architecture Search

• Evolutionary Architecture Search For Deep Multitask Networks.
  Jason Liang, Elliot Meyerson, Risto Miikkulainen.
  Genetic and Evolutionary Computation Conference (GECCO) 2018.
• Transfer Learning to Learn with Multitask Neural Model Search.
  Catherine Wong, Andrea Gesmundo.
  arXiv preprint 2017.

Others

• AutoLoss: Learning Discrete Schedules for Alternate Optimization.
  Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing.
  arXiv preprint 2018.
• Dynamic Task Prioritization for Multitask Learning.
  Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, Li Fei-Fei.
  ECCV 2018.
• Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics.
  Alex Kendall, Yarin Gal, Roberto Cipolla.
  CVPR 2018.
• An Overview of Multi-Task Learning in Deep Neural Networks.
  Sebastian Ruder.
  arXiv preprint 2017.
• A Survey on Multi-Task Learning.
  Yu Zhang, Qiang Yang.
  arXiv preprint 2017.