Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning

Williams, R.J.: Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine learning (1992)

1992

Earlier work this paper cites.

Schmidhuber, J., Zhao, J., Wiering, M.: Shifting inductive bias with success-story algorithm, adaptive levin search, and incremental self-improvement. Machine Learning (1997)

1997

Earlier work this paper cites.

LeCun, Y., Bottou, L., Bengio, Y., Haffner, P., et al.: Gradient-based learning applied to document recognition. Proceedings of the IEEE 86

1998

Earlier work this paper cites.

Kumar, M.P., Packer, B., Koller, D.: Self-paced learning for latent variable models. In: NeurIPS (2010)

2010

Earlier work this paper cites.

Netzer, Y., Wang, T., Coates, A., Bissacco, A., Wu, B., Ng, A.Y.: Reading digits in natural images with unsupervised feature learning (2011)

2011

Earlier work this paper cites.

Gong, B., Shi, Y., Sha, F., Grauman, K.: Geodesic flow kernel for unsupervised domain adaptation. In: CVPR (2012)

2012

Earlier work this paper cites.

Parkhi, O.M., Vedaldi, A., Zisserman, A., Jawahar, C.: Cats and dogs. In: CVPR (2012)

2012

Earlier work this paper cites.

Krause, J., Deng, J., Stark, M., Fei-Fei, L.: Collecting a large-scale dataset of fine-grained cars. The Second Workshop on Fine-Grained Visual Categorization, 2013

2013

Earlier work this paper cites.

Maji, S., Rahtu, E., Kannala, J., Blaschko, M., Vedaldi, A.: Fine-grained visual classification of aircraft. arXiv:1306.5151 (2013)

Original

2013

Earlier work this paper cites.

Berg, T., Liu, J., Woo Lee, S., Alexander, M.L., Jacobs, D.W., Belhumeur, P.N.: Birdsnap: Large-scale fine-grained visual categorization of birds. In: CVPR (2014)

2014

Earlier work this paper cites.

Bossard, L., Guillaumin, M., Van Gool, L.: Food-101–mining discriminative components with random forests. In: ECCV (2014)

2014

Earlier work this paper cites.

Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., , Vedaldi, A.: Describing textures in the wild. In: CVPR (2014)

2014

Earlier work this paper cites.

Girshick, R.B., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: CVPR (2014)

2014

Earlier work this paper cites.

Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. In: ICLR (2014)

2014

Earlier work this paper cites.

Moon, S., Kim, S., Wang, H.: Multimodal transfer deep learning for audio visual recognition. arXiv:1412.3121 (2014)

Original

2014

Earlier work this paper cites.

Razavian, A.S., Azizpour, H., Sullivan, J., Carlsson, S.: CNN features off-the-shelf: an astounding baseline for recognition. In: CVPR (2014)

2014

Earlier work this paper cites.

Hinton, G., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)

Original

2015

Earlier work this paper cites.

Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: CVPR (2015)

2015

Earlier work this paper cites.

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al.: Imagenet large scale visual recognition challenge. IJCV (2015)

2015

Cited alongside, same era.

Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: ICLR (2015)

2015

Cited alongside, same era.

Wang, D., Shen, Z., Shao, J., Zhang, W., Xue, X., Zhang, Z.: Multiple granularity descriptors for fine-grained categorization. In: ICCV (2015)

2015

Cited alongside, same era.

Amodei, D., Anubhai, R., Battenberg, E., Case, C., Casper, J., et al.: Deep speech 2: End-to-end speech recognition in english and mandarin. In: ICML (2016)

2016

Cited alongside, same era.

He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)

2016

Cui, Y., Song, Y., Sun, C., Howard, A., Belongie, S.: Large scale fine-grained categorization and domain-specific transfer learning. In: CVPR (2018)

2018

Later among the works it cites.

Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arxiv:1810.04805 (2018)

Original

2018

Later among the works it cites.

Jenni, S., Favaro, P.: Deep bilevel learning. In: ECCV (2018)

2018

Later among the works it cites.

Jiang, L., Zhou, Z., Leung, T., Li, L., Fei-Fei, L.: Mentornet: Regularizing very deep neural networks on corrupted labels. In: ICML (2018)

2018

Later among the works it cites.

Li, X., Grandvalet, Y., Davoine, F.: Explicit inductive bias for transfer learning with convolutional networks. In: ICML (2018)

2018

Later among the works it cites.