paper-notes

paper notes will be moved to medium for easier publishing

paper notes on machine learning

• Neural Enquirer: Learning to Query Tables with Natural Language

• Modeling documents with Generative Adversarial Networks

• Key-Value Memory Networks for Directly Reading Documents

• Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation[arXiv]

• Glove

2016-11 (ICLR 2017)

Reinforcement Learning:

• A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models [arXiv]
• The Predictron: End-To-End Learning and Planning [OpenReview]
• Third-Person Imitation Learning [OpenReview]
• Generalizing Skills with Semi-Supervised Reinforcement Learning [OpenReview]
• Sample Efficient Actor-Critic with Experience Replay [OpenReview]
• [Reinforcement Learning with Unsupervised Auxiliary Tasks][OpenReview]
• Neural Architecture Search with Reinforcement Learning [OpenReview]
• Towards Information-Seeking Agents [OpenReview]
• Multi-Agent Cooperation and the Emergence of (Natural) Language [OpenReview]
• Improving Policy Gradient by Exploring Under-appreciated Rewards [OpenReview]
• Stochastic Neural Networks for Hierarchical Reinforcement Learning [OpenReview]
• Tuning Recurrent Neural Networks with Reinforcement Learning [OpenReview]
• RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning [arXiv]
• Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning [OpenReview]
• Learning to Perform Physics Experiments via Deep Reinforcement Learning [OpenReview]
• Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU [OpenReview]
• Learning to Compose Words into Sentences with Reinforcement Learning[OpenReview]
• Deep Reinforcement Learning for Accelerating the Convergence Rate [OpenReview]
• Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning [OpenReview]
• Learning to Compose Words into Sentences with Reinforcement Learning [OpenReview]
• Learning to Navigate in Complex Environments [arXiv]
• Unsupervised Perceptual Rewards for Imitation Learning [OpenReview]
• Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic [OpenReview]
• Neural Architecture Search with Reinforcement Learning [OpenReview]

NLP

• Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation [arXiv]
• [Neural Machine Translation with Reconstruction][arXiv]
• Iterative Refinement for Machine Translation [OpenReview]
• A Convolutional Encoder Model for Neural Machine Translation [arXiv]
• Improving Neural Language Models with a Continuous Cache [OpenReview]
• Vocabulary Selection Strategies for Neural Machine Translation [OpenReview]
• Towards an automatic Turing test: Learning to evaluate dialogue responses [OpenReview]
• Dialogue Learning With Human-in-the-Loop [OpenReview]
• Batch Policy Gradient Methods for Improving Neural Conversation Models [OpenReview]
• Learning through Dialogue Interactions [OpenReview]
• [Dual Learning for Machine Translation][arXiv]
• Unsupervised Pretraining for Sequence to Sequence Learning [arXiv]
• On orthogonality and learning recurrent networks with long term dependencies[OpenReview]
• Efficient Vector Representation for Documents through Corruption [OpenReview]
• Generating Long and Diverse Responses with Neural Conversation Models[OpenReview]
• A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks[OpenReview]
• Structured Sequence Modeling with Graph Convolutional Recurrent Networks[OpenReview]
• Wav2Letter: an End-to-End ConvNet-based Speech Recognition System[OpenReview]
• LEARNING A NATURAL LANGUAGE INTERFACE WITH NEURAL PROGRAMMER [OpenReview]
• Dynamic Coattention Networks For Question Answering[OpenReview]
• Quasi-Recurrent Neural Networks[OpenReview]
• A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks [OpenReview]
• Adversarial Training Methods for Semi-Supervised Text Classification[OpenReview]
• A Neural Knowledge Language Model[OpenReview]

One-shot learning/ transfer-learning

• Optimization as a Model for Few-Shot Learning[OpenReview]
• Learning to Remember Rare Events[OpenReview]
• Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks[OpenReview]

CNN

• LOCALLY CONNECTED CONVOLUTIONAL NEURAL NETWORKS ON GRAPH-STRUCTURED DATA[OpenReview]
• Semi-Supervised Classification with Graph Convolutional Networks[OpenReview] semi-supervised learning -Neural Graph Machines: Learning Neural Networks Using Graphs[OpenReview]

misc

• An Analysis of Deep Neural Network Models for Practical Applications[OpenReview]