Semi-supervised learning of compact document representations with deep networks
暂无分享,去创建一个
[1] T. Landauer,et al. Indexing by Latent Semantic Analysis , 1990 .
[2] Stephen E. Robertson,et al. Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval , 1994, SIGIR '94.
[3] Thomas Hofmann,et al. Probabilistic Latent Semantic Analysis , 1999, UAI.
[4] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[5] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[6] Peter V. Gehler,et al. The rate adapting poisson model for information retrieval and object recognition , 2006, ICML.
[7] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[8] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[9] Marc'Aurelio Ranzato,et al. A Unified Energy-Based Framework for Unsupervised Learning , 2007, AISTATS.
[10] Marc'Aurelio Ranzato,et al. Sparse Feature Learning for Deep Belief Networks , 2007, NIPS.
[11] Thomas Hofmann,et al. Greedy Layer-Wise Training of Deep Networks , 2007 .
[12] Yoshua Bengio,et al. Scaling learning algorithms towards AI , 2007 .
[13] Geoffrey E. Hinton,et al. Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes , 2007, NIPS.
[14] Geoffrey E. Hinton,et al. Semantic hashing , 2009, Int. J. Approx. Reason..