不仅是白金赞助商谷歌更是ICML2017的重量级参与者附59篇收录论文下载_[#第一枪]

发布时间：2021-06-07 14:24:15 阅读：次来源：垃圾袋厂家

雷锋网 AI 科技评论按：机器学习领域顶级会议 ICML 2017 已经开始了，雷锋网记者会带来全方位的大会报道。

在之前的文章中，雷锋网 AI 科技评论就介绍过434篇 ICML 收录论文中有多达44篇都出现了谷歌的名字，谷歌的在机器学习领域的投入与成果之多可见一斑。今天谷歌也正式给出了自己的收录论文名单，署名的谷歌的就有42篇，其中有4篇是在几个workshop 中。根据我们前两天的报道，署名DeepMind的收录论文也有25篇之多。那么来自谷歌的全部论文就有65篇（其中2篇是谷歌和DeepMind合作完成的），大约是 ICML 2017 全部收录论文的七分之一。这个数字简直大到让人有点害怕了。

谷歌在文中说，机器学习是谷歌的重点战略之一，他们有非常活跃的研究小组在领域内的各个方面进行研究，包括深度学习和更多的传统算法，理论和应用探索并重。谷歌的研究人员们运用可拓展的工具和架构，构建出各种各样的机器学习系统供他们解决语言、语音、翻译、音乐、视觉处理等等方面艰深的科学和工程问题。

作为机器学习领域的带头人之一，谷歌不仅是今年 ICML 2017的白金赞助商，也实实在在做出了许多研究成果（体现为42篇接收论文），此次参加会议展示论文、组织workshop的研究人员也有130人之多，热切地希望跟整个机器学习大家庭有更多的沟通和协作。

除了论文和workshop，谷歌的研究人员们还会对一些新的研究成果做讲解和展示，比如介绍 Facets 背后的技术、音频生成神经网络 Nsynth，还会有一个关于谷歌大脑培训生计划的问答活动。

谷歌在文中给出了自己的42篇论文列表，感兴趣的读者可以具体关注一下，打包下载地址见文末

A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions

Accelerating Eulerian Fluid Simulation With Convolutional Networks

AdaNet: Adaptive Structural Learning of Artificial Neural Networks

Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP

Algorithms for ?p Low-Rank Approximation

Axiomatic Attribution for Deep Networks

Bridging the Gap Between Value and Policy Based Reinforcement Learning

Lifelong Learning: A Reinforcement Learning Approach Workshop论文，workshop时间8月10日

Canopy Fast Sampling with Cover Trees

Conditional Image Synthesis with Auxiliary Classifier GANs

Consistent k-Clustering

Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs

Density Level Set Estimation on Manifolds with DBSCAN

Device Placement Optimization with Reinforcement Learning

Differentiable Programs with Neural Libraries

Distributed Mean Estimation with Limited Communication

Filtering Variational Objectives

Deep Structured PredictionWorkshop论文，workshop时间8月11日

Generating High-Quality and Informative Conversation Responses with Sequence-to-Sequence Models

Learning to Generate Natural Language Workshop论文，workshop时间8月10日

Geometry of Neural Network Loss Surfaces via Random Matrix Theory

Gradient Boosted Decision Trees for High Dimensional Sparse Output

Input Switched Affine Networks: An RNN Architecture Designed for Interpretability

Large-Scale Evolution of Image Classifiers

Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data

Learned Optimizers that Scale and Generalize

Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo

Learning to Generate Long-term Future via Hierarchical Prediction

Maximum Selection and Ranking under Noisy Comparisons

Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders

谷歌与DeepMind合作论文

Neural Message Passing for Quantum Chemistry

谷歌与DeepMind合作论文

Neural Optimizer Search with Reinforcement Learning

On the Expressive Power of Deep Neural Networks

Online and Linear-Time Attention by Enforcing Monotonic Alignments

Probabilistic Submodular Maximization in Sub-Linear Time

REBAR:Low-variance unbiased gradient estimates for discrete latent variable models

Deep Structured PredictionWorkshop论文，workshop时间8月11日

Robust Adversarial Reinforcement Learning

RobustFill:Neural Program Learning under Noisy IO

Sequence Tutor:Conservative Fine-Tuning of Sequence Generation Models with KL-control

Sharp Minima Can Generalize For Deep Nets

Stochastic Generative Hashing

Tight Bounds for Approximate Carathéodory and Beyond

Uniform Convergence Rates for Kernel Density Estimation

Variational Boosting:Iteratively Refining Posterior Approximations

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning

via Google Research Blog

42篇谷歌署名论文+17篇DeepMind署名演讲论文打包下载链接:

http://pan.baidu.com/s/1jIFYZqu 密码: t74m

AI 科技评论记者也已经在ICML现场参与大会活动，更多报道请继续关注。

太热了，雷锋网跑来悉尼避暑，顺便为你报道 ICML 2017

重磅 | ICML 2017最佳论文公布！机器学习的可解释性成热点

雷锋网版权文章，未经授权禁止转载。详情见转载须知。