2013
Deep Learning
- Adaptive dropout for training deep neural networks. [url]
- [VAE] Auto-Encoding Variational Bayes.
arxiv url :star:
- Better Mixing via Deep Representations. url
- Deep Fisher Networks for Large-Scale Image Classification. [url]
- Deep Learning of Representations-looking forward. [url]
- Deep Neural Networks for Object Detection. [url] :star:
- Dropout Training as Adaptive Regularization. [url]
- Efficient Estimation of Word Representations in Vector Space. [url] :star:
- Exploiting Similarities among Languages for Machine Translation. [url]
- Generalized Denoising Auto-Encoders as Generative Models.
url code
- Generating Sequences With Recurrent Neural Networks.
arxiv :star:
- Generative Stochastic Networks Trainable by Backprop.
arxiv code
- Learning a Deep Compact Image Representation for Visual Tracking. [url]
- Learning Hierarchical Features for Scene Labeling. [url] :star:
- Learning Multi-level Sparse Representations. [url]
- [Maxout] Maxout Networks. [url] :star:
- No More Pesky Learning Rates. [url]
- On autoencoder scoring. [url]
- On the difficulty of training recurrent neural networks. [url]
- On the importance of initialization and momentum in deep learning. [url]
- Provable Bounds for Learning Some Deep Representations.
arxiv :star:
- Regularization of Neural Networks using DropConnect. [url]
- Representation Learning A Review and New Perspectives. [url] :star:
- [RCNN] Rich feature hierarchies for accurate object detection and semantic segmentation.
arxiv code :star:
- Scaling up Spike-and-Slab Models for Unsupervised Feature Learning. [url]
- Speech Recognition with Deep Recurrent Neural Networks.
arxiv :star:
- Stochastic Pooling for Regularization of Deep Convolutional Neural Networks. [url]
- [ZFNet] Visualizing and Understanding Convolutional Networks. [url] :star:
Transfer learning
- Active transfer learning for cross-system recommendation. [pdf]
- Combating Negative Transfer From Predictive Distribution Differences. [url]
- Feature Ensemble Plus Sample Selection: Domain Adaptation for Sentiment Classification. [pdf] :star:
- On handling negative transfer and imbalanced distributions in multiple source transfer learning. [pdf]
- Transfer feature learning with joint distribution adaptation. [pdf]
Deep Reinforcement Learning