An Adaptive Random Path Selection Approach for Incremental Learning

3 Jun 2019Jathushan RajasegaranMunawar HayatSalman KhanFahad Shahbaz KhanLing ShaoMing-Hsuan Yang

In a conventional supervised learning setting, a machine learning model has access to examples of all object classes that are desired to be recognized during the inference stage. This results in a fixed model that lacks the flexibility to adapt to new learning tasks... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.