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人工智能每日论文速递[08.27]

人工智能每日论文速递[08.27]

作者: arXiv每日论文速递 | 来源:发表于2019-08-27 19:30 被阅读0次

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    cs.AI 方向,今日共计31篇

    【1】 Learning Action Models from Disordered and Noisy Plan Traces
    标题:从无序和嘈杂的计划轨迹中学习行动模型
    作者: Hankz Hankui Zhuo, Subbarao Kambhampati
    链接:https://arxiv.org/abs/1908.09800

    【2】 Ensemble approach for natural language question answering problem
    标题:自然语言问答问题的集成方法
    作者: Anna Aniol, Marcin Pietron
    链接:https://arxiv.org/abs/1908.09720

    【3】 Improving Automatic Jazz Melody Generation by Transfer Learning Techniques
    标题:利用迁移学习技术改进爵士乐旋律自动生成
    作者: Hsiao-Tzu Hung, Hsin-Min Wang
    备注:8 pages, Accepted to APSIPA ASC(Asia-Pacific Signal and Information Processing Association Annual Summit and Conference ) 2019
    链接:https://arxiv.org/abs/1908.09484

    【4】 Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning
    标题:深度强化学习中概率图形模型与变分推理的辅导与考察
    作者: Xudong Sun, Bernd Bischl
    链接:https://arxiv.org/abs/1908.09381

    【5】 Dynamics-aware Embeddings
    标题:动态感知嵌入
    作者: William Whitney, Abhinav Gupta
    链接:https://arxiv.org/abs/1908.09357

    【6】 Open Event Extraction from Online Text using a Generative Adversarial Network
    标题:使用生成性对抗网络从在线文本中提取开放事件
    作者: Rui Wang, Yulan He
    备注:Accepted by EMNLP-IJCNLP 2019
    链接:https://arxiv.org/abs/1908.09246

    【7】 Release Strategies and the Social Impacts of Language Models
    标题:发布策略和语言模型的社会影响
    作者: Irene Solaiman, Jasmine Wang
    链接:https://arxiv.org/abs/1908.09203

    【8】 Nearest Neighbor Search-Based Bitwise Source Separation Using Discriminant Winner-Take-All Hashing
    标题:基于最近邻搜索的区分赢家通吃散列的按位信源分离
    作者: Sunwoo Kim, Minje Kim
    链接:https://arxiv.org/abs/1908.09799

    【9】 Once for All: Train One Network and Specialize it for Efficient Deployment
    标题:一劳永逸:培训一个网络并对其进行专业化,以实现高效部署
    作者: Han Cai, Song Han
    链接:https://arxiv.org/abs/1908.09791

    【10】 Differentiable Product Quantization for End-to-End Embedding Compression
    标题:端到端嵌入压缩的可微积量化
    作者: Ting Chen, Yizhou Sun
    链接:https://arxiv.org/abs/1908.09756

    【11】 Preventing the Generation of Inconsistent Sets of Classification Rules
    标题:防止生成不一致的分类规则集
    作者: Thiago Zafalon Miranda, Ricardo Cerri
    链接:https://arxiv.org/abs/1908.09652

    【12】 Semi-supervised Learning for Word Sense Disambiguation
    标题:词义消歧的半监督学习
    作者: Darío Garigliotti
    备注:This work was awarded the Third Place in the EST 2013 Contest (ISSN 1850-2946) at the 42nd JAIIO (Annals of 42nd JAIIO - Argentine Journals of Informatics - ISSN 1850-2776)
    链接:https://arxiv.org/abs/1908.09641

    【13】 Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation
    标题:全局思考,局部行动:基于背景对话的远程监督的全局到本地知识选择
    作者: Pengjie Ren, Maarten de Rijke
    链接:https://arxiv.org/abs/1908.09528

    【14】 Supporting stylists by recommending fashion style
    标题:通过推荐时尚风格来支持造型师
    作者: Tobias Kuhn, Yura Okulovsky
    链接:https://arxiv.org/abs/1908.09493

    【15】 OpenSpiel: A Framework for Reinforcement Learning in Games
    标题:OpenSpiel:游戏中的强化学习框架
    作者: Marc Lanctot, Jonah Ryan-Davis
    链接:https://arxiv.org/abs/1908.09453

    【16】 Improving Neural Story Generation by Targeted Common Sense Grounding
    标题:通过目标常识接地改进神经故事生成
    作者: Huanru Henry Mao, Garrison W. Cottrell
    链接:https://arxiv.org/abs/1908.09451

    【17】 LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm
    标题:LightMC:一种动态高效的多类分解算法
    作者: Ziyu Liu, Tieyan Liu
    链接:https://arxiv.org/abs/1908.09362

    【18】 Exploring the Performance of Deep Residual Networks in Crazyhouse Chess
    标题:Crazyhouse国际象棋中深度残差网络性能的探索
    作者: Sun-Yu Gordon Chi
    链接:https://arxiv.org/abs/1908.09296

    【19】 Generalizing Psychological Similarity Spaces to Unseen Stimuli
    标题:将心理相似空间推广到不可见刺激
    作者: Lucas Bechberger, Kai-Uwe Kühnberger
    链接:https://arxiv.org/abs/1908.09260

    【20】 A Planning Framework for Persistent, Multi-UAV Coverage with Global Deconfliction
    标题:一种具有全局去冲突的持续多无人机覆盖规划框架
    作者: Tushar Kusnur, Maxim Likhachev
    备注:12th Conference on Field and Service Robotics, 2019
    链接:https://arxiv.org/abs/1908.09236

    【21】 Planning Beyond the Sensing Horizon Using a Learned Context
    标题:使用学习的上下文进行超越感知视野的规划
    作者: Michael Everett, Jonathan P. How
    链接:https://arxiv.org/abs/1908.09171

    【22】 A framework for anomaly detection using language modeling, and its applications to finance
    标题:一种使用语言建模的异常检测框架及其在金融中的应用
    作者: Armineh Nourbakhsh, Grace Bang
    备注:5 pages, 2 figures, presented at the 2nd KDD Workshop on Anomaly Detection in Finance, 2019
    链接:https://arxiv.org/abs/1908.09156

    【23】 Hyper-Path-Based Representation Learning for Hyper-Networks
    标题:基于超路径的超网络表示学习
    作者: Jie Huang, Yangqiu Song
    备注:Accepted by CIKM 2019
    链接:https://arxiv.org/abs/1908.09152

    【24】 Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks
    标题:传播选择器:通过图神经网络检测问答支持句
    作者: Seunghyun Yoon, Kyomin Jung
    链接:https://arxiv.org/abs/1908.09137

    【25】 DAST Model: Deciding About Semantic Complexity of a Text
    标题:DAST模型:决定文本的语义复杂性
    作者: MohammadReza Besharati, Mohammad Izadi
    链接:https://arxiv.org/abs/1908.09080

    【26】 Plexus Convolutional Neural Network (PlexusNet): A novel neural networkarchitecture for histologic image analysis
    标题:丛卷积神经网络(PlexusNet):一种用于组织学图像分析的新型神经网络结构
    作者: Okyaz Eminaga, Daniel L. Rubin
    链接:https://arxiv.org/abs/1908.09067

    【27】 Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving
    标题:通用跟踪和概率预测框架及其在自主驾驶中的应用
    作者: Jiachen Li, Masayoshi Tomizuka
    链接:https://arxiv.org/abs/1908.09031

    【28】 Large Scale Organization and Inference of an Imagery Dataset for Public Safety
    标题:公共安全影像数据集的大规模组织与推理
    作者: Jeffrey Liu, Andrew Weinert
    备注:Accepted for publication IEEE HPEC 2019
    链接:https://arxiv.org/abs/1908.09006

    【29】 AIBench: An Industry Standard Internet Service AI Benchmark Suite
    标题:AIBench:一个行业标准的互联网服务AI基准套件
    作者: Wanling Gao, Hainan Ye
    链接:https://arxiv.org/abs/1908.08998

    【30】 MEx: Multi-modal Exercises Dataset for Human Activity Recognition
    标题:MEX:用于人类活动识别的多模态练习数据集
    作者: Anjana Wijekoon, Kay Cooper
    链接:https://arxiv.org/abs/1908.08992

    【31】 EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
    标题:基于正则化图神经网络的EEG情感识别
    作者: Peixiang Zhong, Chunyan Miao
    链接:https://arxiv.org/abs/1907.07835

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