---
res:
  bibo_abstract:
  - "Multi-exit architectures, in which a stack of processing layers is interleaved
    with early output layers, allow the processing of a test example to stop early
    and thus save computation time and/or energy.  In this work, we propose a new
    training procedure for multi-exit architectures based on the principle of knowledge
    distillation. The method encourage searly exits to mimic later, more accurate
    exits, by matching their output probabilities.\r\nExperiments  on  CIFAR100  and
    \ ImageNet  show  that distillation-based training significantly improves the
    accuracy of early exits while maintaining state-of-the-art accuracy  for  late
    \ ones.   The  method  is  particularly  beneficial when  training  data  is  limited
    \ and  it  allows  a  straightforward extension to semi-supervised learning,i.e.
    making use of unlabeled data at training time. Moreover, it takes only afew lines
    to implement and incurs almost no computational overhead at training time, and
    none at all at test time.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Phuong
      foaf_name: Bui Thi Mai, Phuong
      foaf_surname: Bui Thi Mai
      foaf_workInfoHomepage: http://www.librecat.org/personId=3EC6EE64-F248-11E8-B48F-1D18A9856A87
  - foaf_Person:
      foaf_givenName: Christoph
      foaf_name: Lampert, Christoph
      foaf_surname: Lampert
      foaf_workInfoHomepage: http://www.librecat.org/personId=40C20FD2-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0001-8622-7887
  bibo_doi: 10.1109/ICCV.2019.00144
  bibo_volume: 2019-October
  dct_date: 2019^xs_gYear
  dct_identifier:
  - UT:000531438101047
  dct_isPartOf:
  - http://id.crossref.org/issn/1550-5499
  - http://id.crossref.org/issn/9781728148038
  dct_language: eng
  dct_publisher: IEEE@
  dct_title: Distillation-based training for multi-exit architectures@
...