暂无分享,去创建一个
Dumitru Erhan | Honglak Lee | Dragomir Anguelov | Christian Szegedy | Andrew Rabinovich | Scott E. Reed | Christian Szegedy | Dragomir Anguelov | D. Erhan | Andrew Rabinovich | Honglak Lee
[1] Paul Smolensky,et al. Information processing in dynamical systems: foundations of harmony theory , 1986 .
[2] David Yarowsky,et al. Unsupervised Word Sense Disambiguation Rivaling Supervised Methods , 1995, ACL.
[3] Avrim Blum,et al. The Bottleneck , 2021, Monopsony Capitalism.
[4] Carla E. Brodley,et al. Identifying Mislabeled Training Data , 1999, J. Artif. Intell. Res..
[5] Rayid Ghani,et al. Analyzing the effectiveness and applicability of co-training , 2000, CIKM '00.
[6] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[7] Yoshua Bengio,et al. Semi-supervised Learning by Entropy Minimization , 2004, CAP.
[8] Steven P. Abney. Understanding the Yarowsky Algorithm , 2004, CL.
[9] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.
[10] Martial Hebert,et al. Semi-Supervised Self-Training of Object Detection Models , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.
[11] Xiaojin Zhu,et al. Semi-Supervised Learning Literature Survey , 2005 .
[12] Yann LeCun,et al. The mnist database of handwritten digits , 2005 .
[13] Gholamreza Haffari,et al. Analysis of Semi-Supervised Learning with the Yarowsky Algorithm , 2007, UAI.
[14] Yoshua Bengio,et al. Classification using discriminative restricted Boltzmann machines , 2008, ICML '08.
[15] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[16] Estevam R. Hruschka,et al. Toward an Architecture for Never-Ending Language Learning , 2010, AAAI.
[17] Andrew Y. Ng,et al. The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization , 2011, ICML.
[18] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[19] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[20] Anoop Sarkar,et al. Bootstrapping via Graph Propagation , 2012, ACL.
[21] Geoffrey E. Hinton,et al. Learning to Label Aerial Images from Noisy Data , 2012, ICML.
[22] Pascal Vincent,et al. Disentangling Factors of Variation for Facial Expression Recognition , 2012, ECCV.
[23] Xinlei Chen,et al. NEIL: Extracting Visual Knowledge from Web Data , 2013, 2013 IEEE International Conference on Computer Vision.
[24] Yoshua Bengio,et al. Multi-Prediction Deep Boltzmann Machines , 2013, NIPS.
[25] Dong-Hyun Lee,et al. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks , 2013 .
[26] Rob Fergus,et al. Visualizing and Understanding Convolutional Neural Networks , 2013 .
[27] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[28] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Dumitru Erhan,et al. Scalable, High-Quality Object Detection , 2014, ArXiv.
[30] Xiaogang Wang,et al. DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection , 2014, ArXiv.
[31] R. Fergus,et al. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks , 2013, ICLR.
[32] Yoshua Bengio,et al. Deep Generative Stochastic Networks Trainable by Backprop , 2013, ICML.
[33] Dumitru Erhan,et al. Scalable Object Detection Using Deep Neural Networks , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[34] Yuting Zhang,et al. Learning to Disentangle Factors of Variation with Manifold Interaction , 2014, ICML.
[35] Joan Bruna,et al. Training Convolutional Networks with Noisy Labels , 2014, ICLR 2014.
[36] Xinlei Chen,et al. Enriching Visual Knowledge Bases via Object Discovery and Segmentation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Rob Fergus,et al. Learning from Noisy Labels with Deep Neural Networks , 2014, ICLR.
[38] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[40] Yves Grandvalet Yoshua. 9 Entropy Regularization , 2022 .