2019年重要会议顶会AAAI ICML ICLR IJCAI NIPS 重要文章汇总以及录用目录

AAAI2019 录用文章目录http://www.aaai.org/Library/AAAI/aaai19contents.php

AAAI 2019 杰出论文奖
How to Combine Tree-Search Methods in Reinforcement Learning

AAAI 2019 杰出论文奖荣誉提名
Solving Imperfect-Information Games via Discounted Regret Minimization

AAAI 2019 杰出学生论文奖
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference

AAAI 2019 杰出学生论文奖荣誉提名
Learning to Teach in Cooperative Multiagent Reinforcement Learning

ICLR2019录用文章目录 https://chillee.github.io/OpenReviewExplorer/index.html?conf=iclr2019

ICLR 2019
两篇最佳论文
1.有序神经元:将树结构集成到循环神经网络 Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
2.彩票假设:寻找稀疏的、可训练的神经网络 The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
几篇高分论文:
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Slimmable Neural Networks
Posterior Attention Models for Sequence to Sequence Learning
 

ICML 2019 https://icml.cc/Conferences/2019/Schedule?type=Poster 
两篇 最佳论文
1.挑战无监督解耦表示中的常见假设  Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
2.稀疏高斯过程回归变分的收敛速度 Rates of Convergence for Sparse Variational Gaussian Process Regression
7篇 提名奖
1.类比可解释性:趋向理解词嵌入 Analogies Explained: Towards Understanding Word Embeddings
2.SATNet:使用差分可满足性求解器来桥接深度学习和逻辑推理 SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
3.深度神经网络中随机梯度噪声的尾指数分析 A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
4.趋向随机傅里叶特征的统一分析 Towards A Unified Analysis of Random Fourier Features
5.分期偿还的蒙特卡罗积分 Amortized Monte Carlo Integration
6.多智能体深度强化学习的内在动机的社会影响 Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
7.随机波束以及找到它们的地方:取样序列无需更换的 Gumbel-Top-k 方法 Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
 

IJCAI 2019 录用文章目录 https://www.ijcai.org/Proceedings/2019/

IJCAI2019
一篇杰出论文 (Distinguished Paper)
Boosting for Comparison-Based Learning
 IJCAI-JAIR 最佳论文
Clause Elimination for SAT and QSAT

NIPS 2019 录用文章目录 https://nips.cc/Conferences/2019/Schedule?type=Poster

NIP2019
杰出论文奖
论文名称:Distribution-Independent PAC Learning of Halfspaces with Massart Noise

杰出新方向论文奖
论文名称:Uniform convergence may be unable to explain generalization in deep learning

杰出论文奖荣誉提名
论文名称:Nonparametric density estimation & convergence of GANs under Besov IPM losses

杰出新方向论文奖荣誉提名
论文名称:Putting An End to End-to-End: Gradient-Isolated Learning of Representations

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