Program Synthesis for Character Level Language Modeling
作者: Pavol Bielik, Veselin Raychev, Martin Vechev
Words or Characters? Fine-grained Gating for Reading Comprehension
作者: Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov
Deep Character-Level Neural Machine Translation By Learning Morphology
作者: Shenjian Zhao, Zhihua Zhang
Opening the vocabulary of neural language models with character-level word representations
作者: Matthieu Labeau, Alexandre Allauzen
Unsupervised sentence representation learning with adversarial auto-encoder
作者: Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang
Offline Bilingual Word Vectors Without a Dictionary
作者: Samuel L. Smith, David H. P. Turban, Nils Y. Hammerla, Steven Hamblin
Learning Word-Like Units from Joint Audio-Visual Analylsis
作者:David Harwath, James R. Glass
Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling
作者: Hakan Inan, Khashayar Khosravi, Richard Socher
Learning to Query, Reason, and Answer Questions On Ambiguous Texts
作者: Xiaoxiao Guo, Tim Klinger, Clemens Rosenbaum, Joseph P. Bigus, Murray Campbell, Ban Kawas, Kartik Talamadupula, Gerry Tesauro, Satinder Singh
Group Sparse CNNs for Question Sentence Classification with Answer Sets
作者: Mingbo Ma, Liang Huang, Bing Xiang, Bowen Zhou
CONTENT2VEC: Specializing Joint Representations of Product Images and Text for the task of Product Recommendation
作者: Thomas Nedelec, Elena Smirnova, Flavian Vasile
Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce
作者: Tom Zahavy, Alessandro Magnani, Abhinandan Krishnan, Shie Mannor
3.词/句嵌入
A Simple but Tough-to-Beat Baseline for Sentence Embeddings
作者: Sanjeev Arora, Yingyu Liang, Tengyu Ma
Investigating Different Context Types and Representations for Learning Word Embeddings
3. Unsupervised sentence representation learning with adversarial auto-encoder
作者: Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang
4. Tree-Structured Variational Autoencoder
作者: Richard Shin, Alexander A. Alemi, Geoffrey Irving, Oriol Vinyals
5. Lossy Image Compression with Compressive Autoencoders
作者: Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
6. Variational Lossy Autoencoder
作者: Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
7. Stick-Breaking Variational Autoencoders
作者: Eric Nalisnick, Padhraic Smyth
8. ParMAC: distributed optimisation of nested functions, with application to binary autoencoders
作者: Miguel A. Carreira-Perpinan, Mehdi Alizadeh
9. Discrete Variational Autoencoders 作者: Jason Tyler Rolfe
10. Deep Unsupervised Clustering with Gaussian Mixture\Variational Autoencoders
作者: Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew,C.H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan
11. Improving Sampling from Generative Autoencoders with Markov Chains
作者: Kai Arulkumaran, Antonia Creswell, Anil Anthony Bharath
ICLR 2017 —增强学习深度学习论文
以下论文均可在https://amundtveit.com/直接下载
Stochastic Neural Networks for Hierarchical Reinforcement Learning
作者: Carlos Florensa, Yan Duan, Pieter Abbeel
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
作者: Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi C
hen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning
作者: Abhishek Gupta, Coline Devin, YuXuan Liu, Pieter Abbeel, Se
rgey Levine
Deep Reinforcement Learning for Accelerating the Convergence Rate
作者: Jie Fu, Zichuan Lin, Danlu Chen, Ritchie Ng, Miao Liu, Nicholas Leonard, Jiashi Feng, Tat-Seng Chua
Generalizing Skills with Semi-Supervised Reinforcement Learning
作者: Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
Learning to Perform Physics Experiments via Deep Reinforcement Learning – 作者: Misha Denil, Pulkit Agrawal, Tejas D Kulkarni, Tom Erez, Peter Batta
glia, Nando de Freitas
Reinforcement Learning with Unsupervised Auxiliary Tasks
作者: Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z Leibo,David Silver, Koray Kavukcuoglu
Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU
作者: Mohammad Babaeizadeh, Iuri Frosio, Stephen Tyree, Jason Clemons,Jan Kautz
Multi-task learning with deep model based reinforcement learning
作者:Asier Mujika
Neural Architecture Search with Reinforcement Learning
作者:: Barret Zoph, Quoc Le
Tuning Recurrent Neural Networks with Reinforcement Learning
作者:: Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck
RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning
作者: Yan Duan, John Schulman, Xi Chen, Peter Bartlett, Ilya Sutskever, Pieter Abbeel
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning
作者: Sahil Sharma, Aravind S. Lakshminarayanan, Balaraman Ravindran
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
作者: Frank S.He, Yang Liu, Alexander G. Schwing, Jian Peng
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
作者: Joshua Achiam, Shankar Sastry
Learning to Compose Words into Sentences with Reinforcement Learning
作者:Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling
Spatio-Temporal Abstractions in Reinforcement Learning Through Neural Encoding
作者: Nir Baram, Tom Zahavy, Shie Mannor
Modular Multitask Reinforcement Learning with Policy Sketches
作者:Jacob Andreas, Dan Klein, Sergey Levine
Combating Deep Reinforcement Learning’s Sisyphean Curse with Intrinsic Fear 作者:Zachary C. Lipton, Jianfeng Gao, Lihong Li, Jianshu Chen, Li Deng
(推荐关注)
ICLR 2017 生成和对抗式生成论文(45篇)
以下论文均可在https://amundtveit.com/直接下载
Unsupervised Learning Using Generative Adversarial Training And Clustering
作者: Vittal Premachandran, Alan L. Yuille
Improving Generative Adversarial Networks with Denoising Feature Matching
作者: David Warde-Farley, Yoshua Bengio
Generative Adversarial Parallelization
作者: Daniel Jiwoong Im, He Ma, Chris Dongjoo Kim, Graham Taylor
Adversarial examples for generative models
作者: Jernej Kos, Dawn Song
Mode Regularized Generative Adversarial Networks
作者: Tong Che, Yanran Li, Athul Jacob, Yoshua Bengio, Wenjie Li
Variational Recurrent Adversarial Deep Domain Adaptation
作者:: Sanjay Purushotham, Wilka Carvalho, Tanachat Nilanon, Yan Liu
Structured Interpretation of Deep Generative Models
作者: N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank Wood, Noah D. Goodman, Pushmeet Kohli, Philip H.S. Torr
Inference and Introspection in Deep Generative Models of Sparse Data
作者:Rahul G. Krishnan, Matthew Hoffman
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
作者: Dougal J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, Arthur Gretton
Unsupervised sentence representation learning with adversarial auto-encoder
作者: Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang
Unsupervised Program Induction with Hierarchical Generative Convolutional Neural Networks
作者: Qucheng Gong, Yuandong Tian, C. Lawrence Zitnick
A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Noise
作者: Beilun Wang, Ji Gao, Yanjun Qi
On the Quantitative Analysis of Decoder-Based Generative Models
作者: Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger Grosse
Evaluation of Defensive Methods for DNNs against Multiple Adversarial Evasion Models
作者:Xinyun Chen, Bo Li, Yevgeniy Vorobeychik
Calibrating Energy-based Generative Adversarial Networks
作者: Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard Hovy, Aaron Courville
Inverse Problems in Computer Vision using Adversarial Imagination Priors
作者: Hsiao-Yu Fish Tung, Katerina Fragkiadaki
Towards Principled Methods for Training Generative Adversarial Networks作者: Martin Arjovsky, Leon Bottou
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
作者: Dilin Wang, Qiang Liu
Adversarial Machine Learning at Scale
作者: Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
Adversarial Training Methods for Semi-Supervised Text Classification
作者: Takeru Miyato, Andrew M. Dai, Ian Goodfellow
Sampling Generative Networks: Notes on a Few Effective Techniques
作者: Tom White
Adversarial examples in the physical world
作者: Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
Improving Sampling from Generative Autoencoders with Markov Chains
作者:Kai Arulkumaran, Antonia Creswell, Anil Anthony Bharath
Neural Photo Editing with Introspective Adversarial Networks
作者: Andrew Brock, Theodore Lim, J.M. Ritchie, Nick Weston
Learning to Protect Communications with Adversarial Neural Cryptography
作者: Martín Abadi, David G.
ICLR 2017 -随机/策略梯度论文
以下论文均可在https://amundtveit.com/直接下载
Improving Policy Gradient by Exploring Under-appreciated Rewards
作者:: Ofir Nachum, Mohammad Norouzi, Dale Schuurmans
Leveraging Asynchronicity in Gradient Descent for Scalable Deep Learning
作者:Jeff Daily, Abhinav Vishnu, Charles Siegel
Adding Gradient Noise Improves Learning for Very Deep Networks
作者:: Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Lukasz Kaiser, Karol Kurach, Ilya Sutskever, James Martens
Inefficiency of stochastic gradient descent with larger mini-batches (and more learners)
作者: Onkar Bhardwaj, Guojing Cong
SGDR: Stochastic Gradient Descent with Restarts
作者: Ilya Loshchilov, Frank Hutter
Neural Data Filter for Bootstrapping Stochastic Gradient Descent
作者: Yang Fan, Fei Tian, Tao Qin, Tie-Yan Liu
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys 作者: Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun (推荐关注)
Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
作者: Shixiang Gu, Timothy Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
Batch Policy Gradient Methods for Improving Neural Conversation Models
作者:Kirthevasan Kandasamy, Yoram Bachrach, Ryota Tomioka, Daniel Tarlow, David Carter
Training Long Short-Term Memory With Sparsified Stochastic Gradient Descent 作者:: Maohua Zhu, Minsoo Rhu, Jason Clemons, Stephen W. Keckler, Yuan Xie(推荐关注)