🤖 Machine Learning Papers

Deep Residual Learning for Image Recognition

Kaiming He, Xiangyu Zhang et al. (2016)

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Random Forests

Leo Breiman (2001)

Machine Learning

Deep learning

Yann LeCun, Yoshua Bengio et al. (2015)

Nature

Gradient-based learning applied to document recognition

Y. Lecun, L. Bottou et al. (1998)

Proceedings of the IEEE

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He et al. (2017)

IEEE Transactions on Pattern Analysis and Machine Intelligence

Situated Learning

Jean Lave, Etienne Wenger (1991)

Support-vector networks

Corinna Cortes, Vladimir Vapnik (1995)

Machine Learning

Learning representations by back-propagating errors

David E. Rumelhart, Geoffrey E. Hinton et al. (1986)

Nature

Absorptive Capacity: A New Perspective on Learning and Innovation

Wesley M. Cohen, Daniel A. Levinthal (1990)

Administrative Science Quarterly

Human-level control through deep reinforcement learning

Volodymyr Mnih, Koray Kavukcuoglu et al. (2015)

Nature

The Elements of Statistical Learning

Trevor Hastie, Robert Tibshirani et al. (2009)

Springer Series in Statistics

A Computational Approach to Edge Detection

John Canny (1986)

IEEE Transactions on Pattern Analysis and Machine Intelligence

Greedy function approximation: A gradient boosting machine.

Jerome H. Friedman (2001)

The Annals of Statistics

Communities of Practice

Etienne Wenger (1998)

A Survey on Transfer Learning

Sinno Jialin Pan, Qiang Yang (2010)

IEEE Transactions on Knowledge and Data Engineering