2013

Deep Learning

Adaptive dropout for training deep neural networks. [url]
[VAE] Auto-Encoding Variational Bayes. arxiv url ⭐
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] ⭐
Dropout Training as Adaptive Regularization. [url]
Efficient Estimation of Word Representations in Vector Space. [url] ⭐
Exploiting Similarities among Languages for Machine Translation. [url]
Generalized Denoising Auto-Encoders as Generative Models. url code
Generating Sequences With Recurrent Neural Networks. arxiv ⭐
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] ⭐
Learning Multi-level Sparse Representations. [url]
[Maxout] Maxout Networks. [url] ⭐
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 ⭐
Regularization of Neural Networks using DropConnect. [url]
Representation Learning A Review and New Perspectives. [url] ⭐
[RCNN] Rich feature hierarchies for accurate object detection and semantic segmentation. arxiv code ⭐
Scaling up Spike-and-Slab Models for Unsupervised Feature Learning. [url]
Speech Recognition with Deep Recurrent Neural Networks. arxiv ⭐
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks. [url]
[ZFNet] Visualizing and Understanding Convolutional Networks. [url] ⭐

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] ⭐
On handling negative transfer and imbalanced distributions in multiple source transfer learning. [pdf]
Transfer feature learning with joint distribution adaptation. [pdf]

Deep Reinforcement Learning

Evolving large-scale neural networks for vision-based reinforcement learning. [idsia] ⭐
Playing Atari with Deep Reinforcement Learning. [toronto] ⭐