Papers
Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing
Chen Liang, Mohammad Norouzi, Jonathan Berant et al.
Memory Based Online Learning of Deep Representations From Video Streams
Federico Pernici, Federico Bartoli, Matteo Bruni et al.
Memory-based Parameter Adaptation
Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae et al.
Memory Matching Networks for One-Shot Image Recognition
Qi Cai, Yingwei Pan, Ting Yao et al.
Memory Replay GANs: Learning to Generate New Categories without Forgetting
Chenshen Wu, Luis Herranz, Xialei Liu et al.
Memory, Show the Way: Memory Based Few Shot Word Representation Learning
Jingyuan Sun, Shaonan Wang, Chengqing Zong
Memory Time Span in LSTMs for Multi-Speaker Source Separation
Jeroen Zegers, Hugo van Hamme
MEnet: A Metric Expression Network for Salient Object Segmentation
Shulian Cai, Jiabin Huang, Delu Zeng et al.
Mental Sampling in Multimodal Representations
Jianqiao Zhu, Adam Sanborn, Nick Chater
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang, Zhengyuan Zhou, Thomas Leung et al.
Merging Datasets for Aggressive Text Identification
Paula Fortuna, José Ferreira, Luiz Pires et al.
MeSH-based dataset for measuring the relevance of text retrieval
Won Gyu Kim, Lana Yeganova, Donald Comeau et al.
Mesh-TensorFlow: Deep Learning for Supercomputers
Noam Shazeer, Youlong Cheng, Niki Parmar et al.
Mesoscopic Facial Geometry Inference Using Deep Neural Networks
Loc Huynh, Weikai Chen, Shunsuke Saito et al.
Message Passing Stein Variational Gradient Descent
Jingwei Zhuo, Chang Liu, Jiaxin Shi et al.
MetaAnchor: Learning to Detect Objects with Customized Anchors
Tong Yang, Xiangyu Zhang, Zeming Li et al.
Metadata-dependent Infinite Poisson Factorization for Efficiently Modelling Sparse and Large Matrices in Recommendation
Trong Dinh Thac Do, Longbing Cao
MetaGAN: An Adversarial Approach to Few-Shot Learning
Ruixiang ZHANG, Tong Che, Zoubin Ghahramani et al.
Meta-Gradient Reinforcement Learning
Zhongwen Xu, Hado P van Hasselt, David Silver
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm
Chelsea Finn, Sergey Levine
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
Ron Amit, Ron Meir
Meta-Learning for Low-Resource Neural Machine Translation
Jiatao Gu, Yong Wang, Yun Chen et al.
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren, Eleni Triantafillou, Sachin Ravi et al.
Meta-Learning MCMC Proposals
Tongzhou Wang, YI WU, Dave Moore et al.