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历史文章列表 网站https://www.arxivdaily.com/
注：含中英文摘要速递见公众号【arXiv每日学术速递】,涵盖CS|物理|数学|经济|统计|金融|生物|电气等领域。 cs.AI人工智能，共计48篇
【1】 Capabilities for Better ML Engineering
标题：更好的ML工程的能力
链接：https://arxiv.org/abs/2211.06409
作者：Chenyang Yang,Rachel Brower-Sinning,Grace A. Lewis,Christian Kästner,Tongshuang Wu
机构：School of Computer Science, Carnegie Mellon University, Carnegie Mellon Software Engineering Institute
【2】 Control Transformer: Robot Navigation in Unknown Environments through PRM-Guided Return-Conditioned Sequence Modeling
标题：控制Transformer：基于PRM引导的返回条件序列建模的未知环境下的机器人导航
链接：https://arxiv.org/abs/2211.06407
作者：Daniel Lawson,Ahmed H. Qureshi
机构： but in a way that thispolicy does not need to rely on external planning duringThe authors are with the Department of Computer Science, PurdueUniversity
【3】 Behaviour Trees for Conversational Explanation Experiences
标题：对话解释体验的行为树
链接：https://arxiv.org/abs/2211.06402
作者：Anjana Wijekoon,David Corsar,Nirmalie Wiratunga
机构：School of Computing, Robert Gordon University, Aberdeen, Scotland
【4】 STAR: A Session-Based Time-Aware Recommender System
标题：STAR：一种基于会话的时间感知推荐系统
链接：https://arxiv.org/abs/2211.06394
作者：Reza Yeganegi,Saman Haratizadeh
机构：University of Tehran, Tehran, Iran
【5】 Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning
标题：能力感知型深度强化学习兴趣度的全局和局部分析
链接：https://arxiv.org/abs/2211.06376
作者：Pedro Sequeira,Jesse Hostetler,Melinda Gervasio
机构：SRI International, Ravenswood Ave., Menlo Park, CA
备注：Appears in Proceedings of AAAI FSS-22 Symposium "Lessons Learned for Autonomous Assessment of Machine Abilities (LLAAMA)"
【6】 Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates
标题：将推荐系统置于实践中：走向归纳学习和增量更新
链接：https://arxiv.org/abs/2211.06365
作者：Tobias Schnabel,Mengting Wan,Longqi Yang
【7】 Emergency action termination for immediate reaction in hierarchical reinforcement learning
标题：分层强化学习中即时反应的紧急动作终止
链接：https://arxiv.org/abs/2211.06351
作者：Michał Bortkiewicz,Jakub Łyskawa,Paweł Wawrzyński,Mateusz Ostaszewski,Artur Grudkowski,Tomasz Trzciński
机构：Warsaw University of Technology, Institute of Computer Science,Ensavid, Jagiellonian University,Tooploox,IDEAS NCBR
【8】 AI Ethics in Smart Healthcare
标题：智能医疗中的人工智能伦理
链接：https://arxiv.org/abs/2211.06346
作者：Sudeep Pasricha
机构：Colorado State University
【9】 Runtime data center temperature prediction using Grammatical Evolution techniques
标题：基于语法进化技术的运行时数据中心温度预测
链接：https://arxiv.org/abs/2211.06329
作者：Marina Zapater,José L. Risco-Martín,Patricia Arroba,José L. Ayala,José M. Moya,Román Hermida
机构：DACYA, Universidad Complutense de Madrid, Madrid , Spain, CCS - Center for Computational Simulation, Campus de Montegancedo UPM, Spain, LSI - Integrated Systems Lab., Universidad Polit´ecnica de Madrid, Madrid , Spain
【10】 Secure Aggregation Is Not All You Need: Mitigating Privacy Attacks with Noise Tolerance in Federated Learning
标题：安全聚合并不是您需要的全部：联合学习中的噪声容忍缓解隐私攻击
链接：https://arxiv.org/abs/2211.06324
作者：John Reuben Gilbert
机构：Advisor: Professor Yen-Jen Oyang, Graduate Institute of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, arXiv:,.,v, [cs.CR] , Nov
备注：Master Thesis
【11】 Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
标题：人工智能与2030年的生活：人工智能百年研究
链接：https://arxiv.org/abs/2211.06318
作者：Peter Stone,Rodney Brooks,Erik Brynjolfsson,Ryan Calo,Oren Etzioni,Greg Hager,Julia Hirschberg,Shivaram Kalyanakrishnan,Ece Kamar,Sarit Kraus,Kevin Leyton-Brown,David Parkes,William Press,AnnaLee Saxenian,Julie Shah,Milind Tambe,Astro Teller
机构： The One Hundred Year Study was subsequently endowed at a university to enable 1 “One Hundred Year Study on Artificial Intelligence (AI 100), ” Stanford University
备注：52 pages, this https URL
【12】 Fradulent User Detection Via Behavior Information Aggregation Network (BIAN) On Large-Scale Financial Social Network
标题：基于行为信息聚合网络的大规模金融社交网络欺诈用户检测
链接：https://arxiv.org/abs/2211.06315
作者：Hanyi Hu,Long Zhang,Shuan Li,Zhi Liu,Yao Yang,Chongning Na
机构：Fintech Research Center, Zhejiang Lab
备注：6 pages, 1 figure
【13】 Do Bayesian Neural Networks Need To Be Fully Stochastic?
标题：贝叶斯神经网络需要是完全随机的吗？
链接：https://arxiv.org/abs/2211.06291
作者：Mrinank Sharma,Sebastian Farquhar,Eric Nalisnick,Tom Rainforth
机构：University of Oxford, University of Amsterdam
【14】 A hybrid entity-centric approach to Persian pronoun resolution
标题：一种以实体为中心的混合波斯语代词解析方法
链接：https://arxiv.org/abs/2211.06257
作者：Hassan Haji Mohammadi,Alireza Talebpour,Ahmad Mahmoudi Aznaveh,Samaneh Yazdani
机构：a Islamic Azad University Tehran North Branch, Tehran, Iran, b Shahid Beheshti University, Tehran, Iran
备注：27 pages
【15】 Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization
标题：预测处理近邻策略优化的高效深度强化学习
链接：https://arxiv.org/abs/2211.06236
作者：Burcu Küçükoğlu,Walraaf Borkent,Bodo Rueckauer,Nasir Ahmad,Umut Güçlü,Marcel van Gerven
机构：Umut G¨u¸cl¨u, Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
备注：17 pages, 6 figures
【16】 HOReeNet: 3D-aware Hand-Object Grasping Reenactment
标题：HOReeNet：3D感知的手-物体抓取再现
链接：https://arxiv.org/abs/2211.06195
作者：Changhwa Lee,Junuk Cha,Hansol Lee,Seongyeong Lee,Donguk Kim,Seungryul Baek
机构：UNIST, South Korea, Kakao Brain Corp, South Korea, NC Soft, South Korea
备注：5 pages, 5 figures
【17】 REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study
标题：测量黑盒模型局部线性解释的狂欢框架：深度学习图像分类研究案例
链接：https://arxiv.org/abs/2211.06154
作者：Iván Sevillano-García,Julián Luengo-Martín,Francisco Herrera
机构：DaSCI, University of Granada, Granada, Spain, King Abdulaziz University, Jeddah, Saudi Arabia
【18】 Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning Approach
标题：扩展共享电子移动系统的车队再平衡：一种多智能体深度强化学习方法
链接：https://arxiv.org/abs/2211.06136
作者：Man Luo,Bowen Du,Wenzhe Zhang,Tianyou Song,Kun Li,Hongming Zhu,Mark Birkin,Hongkai Wen
机构： University of Exeter, UK, The Alan Turing Institute, UK, University of Warwick, UK, University of California San Diego, US, University of Illinois Urbana-Champaign, US, Columbia University, US, Tongji University, China, University of Leeds, UK
【19】 Active Task Randomization: Learning Visuomotor Skills for Sequential Manipulation by Proposing Feasible and Novel Tasks
标题：主动任务随机化：通过提出可行和新颖的任务来学习顺序操作的视觉运动技能
链接：https://arxiv.org/abs/2211.06134
作者：Kuan Fang,Toki Migimatsu,Ajay Mandlekar,Li Fei-Fei,Jeannette Bohg
机构： 1University of California, 2Stanford University, Toyota Research Institute provided funds to support this work
备注：9 pages, 5 figures
【20】 English Contrastive Learning Can Learn Universal Cross-lingual Sentence Embeddings
标题：英语对比学习可以学习普遍的跨语言句子嵌入
链接：https://arxiv.org/abs/2211.06127
作者：Yau-Shian Wang,Ashley Wu,Graham Neubig
机构：Carnegie Mellon University
备注：accepted by EMNLP 2022
【21】 Towards automating Numerical Consistency Checks in Financial Reports
标题：走向财务报告中数字一致性检查的自动化
链接：https://arxiv.org/abs/2211.06112
作者：Lars Hillebrand,Tobias Deußer,Tim Dilmaghani,Bernd Kliem,Rüdiger Loitz,Christian Bauckhage,Rafet Sifa
机构：†Fraunhofer IAIS, Bonn, Germany, ‡University of Bonn, Bonn, Germany, §PricewaterhouseCoopers GmbH, D¨usseldorf, Germany
备注：Accepted at BigData 2022, 10 pages, 3 figure, 5 tables
【22】 RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection System
标题：RaLiBEV：锚箱自由目标检测系统中雷达与激光雷达的融合学习
链接：https://arxiv.org/abs/2211.06108
作者：Yanlong Yang,Jianan Liu,Tao Huang,Qing-Long Han,Gang Ma,Bing Zhu
机构： Swinburne University of Technology
【23】 Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models
标题：识别、测量和缓解监督学习模型的个体不公平性及其在信用风险模型中的应用
链接：https://arxiv.org/abs/2211.06106
作者：Rasoul Shahsavarifar,Jithu Chandran,Mario Inchiosa,Amit Deshpande,Mario Schlener,Vishal Gossain,Yara Elias,Vinaya Murali
机构：Executive Summary
备注：12 pages, 3 figures
【24】 Interactive Context-Aware Network for RGB-T Salient Object Detection
标题：用于RGB-T显著目标检测的交互式上下文感知网络
链接：https://arxiv.org/abs/2211.06097
作者：Yuxuan Wang,Feng Dong,Jinchao Zhu
机构：College of Artificial Intelligence, Nankai University, Tongyan, Tianjin, China., School of Finance, Tianjin University of Finance and Economics, Tianjin, China., Department of Automation, Tsinghua University, Beijing, China.
备注：17 pages, 7 figures
【25】 Does Deep Learning REALLY Outperform Non-deep Machine Learning for Clinical Prediction on Physiological Time Series?
标题：对于生理时间序列的临床预测，深度学习真的优于非深度机器学习吗？
链接：https://arxiv.org/abs/2211.06034
作者：Ke Liao,Wei Wang,Armagan Elibol,Lingzhong Meng,Xu Zhao,Nak Young Chong
机构：YaleUniversitySchoolofMedicine
【26】 Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention
标题：SNN和ANN的舞蹈：结合脉冲计时和重建注意力解决绑定问题
链接：https://arxiv.org/abs/2211.06027
作者：Hao Zheng,Hui Lin,Rong Zhao,Luping Shi
机构：Department of Precision Instrument, Center for Brain-Inspired Computing Research, Tsinghua University, Beijing , China
【27】 Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction
标题：用于一般低资源信息提取的梯度模仿强化学习
链接：https://arxiv.org/abs/2211.06014
作者：Xuming Hu,Shiao Meng,Chenwei Zhang,Xiangli Yang,Lijie Wen,Irwin King,Philip S. Yu
机构： Yang is with the School of Computer Science and Engineering, University of Electronic Science and Technology of China
备注：This work has been submitted to the IEEE for possible publication. arXiv admin note: text overlap with arXiv:2109.06415
【28】 GeoAI for Knowledge Graph Construction: Identifying Causality Between Cascading Events to Support Environmental Resilience Research
标题：用于构建知识图的GeoAI：识别级联事件之间的因果关系以支持环境弹性研究
链接：https://arxiv.org/abs/2211.06011
作者：Yuanyuan Tian,Wenwen Li
机构：School of Geographical Science and Urban Planning, Arizona State University, Tempe, AZ, USA
【29】 What's the Situation with Intelligent Mesh Generation: A Survey and Perspectives
标题：智能网格生成的现状：综述与展望
链接：https://arxiv.org/abs/2211.06009
作者：Zezeng Li,Zebin Xu,Ying Li,Xianfeng Gu,Na Lei
【30】 MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering
标题：MF2-MVQA：一种面向医学视觉问答的多阶段特征融合方法
链接：https://arxiv.org/abs/2211.05991
作者：Shanshan Song,Jiangyun Li,Jing Wang,Yuanxiu Cai,Wenkai Dong
机构：a School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China b Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education
【31】 Misinformation Detection using Persuasive Writing Strategies
标题：基于说服性写作策略的错误信息检测
链接：https://arxiv.org/abs/2211.05985
作者：Joseph Romain,Huiyi Liu,Wei Peng,Jingbo Meng,Parisa Kordjamshidi
机构： Department of Computer Science and Engineering, Michigan State University, Department of Communication, Michigan State University, Department of Media and Information, Michigan State University, School of Communication, Ohio State University
【32】 Breadth-First Pipeline Parallelism
标题：广度优先流水线并行性
链接：https://arxiv.org/abs/2211.05953
作者：Joel Lamy-Poirier
【33】 CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
标题：CR-LSO：输入凸神经网络图变分自动编码器潜在空间的凸神经结构优化
链接：https://arxiv.org/abs/2211.05950
作者：Xuan Rao,Bo Zhao,Xiaosong Yi,Derong Liu
机构：Guangdong University of Technology,Beijing Normal University, Southern University of Science and Technology,University of Illinois at Chicago
【34】 Deep Reinforcement Learning Microgrid Optimization Strategy Considering Priority Flexible Demand Side
标题：考虑需求侧优先柔性的深度强化学习微电网优化策略
链接：https://arxiv.org/abs/2211.05946
作者：Jinsong Sang,Hongbin Sun,Lei Kou
机构：Changchun Institute of Technology, School of Electrical Engineering, National and Local Joint Engineering Research Center for Smart, Distribution Network Measurement, Control and Safe Operation, Technology, Changchun , China
备注：Sensors
【35】 A Gait Triaging Toolkit for Overlapping Acoustic Events in Indoor Environments
标题：室内环境中交叠声事件步态检测工具包
链接：https://arxiv.org/abs/2211.05944
作者：Kelvin Summoogum,Debayan Das,Parvati Jayakumar
备注：5 pages
【36】 pyRDDLGym: From RDDL to Gym Environments
标题：PyRDDLGym：从RDDL环境到Gym环境
链接：https://arxiv.org/abs/2211.05939
作者：Ayal Taitler,Michael Gimelfarb,Sriram Gopalakrishnan,Martin Mladenov,Xiaotian Liu,Scott Sanner
机构：University of Toronto, CA, J.P. Morgan AI Research, Google, BR
【37】 Inferring probabilistic Boolean networks from steady-state gene data samples
标题：从稳态基因数据样本推断概率布尔网络
链接：https://arxiv.org/abs/2211.05935
作者：Vytenis Šliogeris,Leandros Maglaras,Sotiris Moschoyiannis
【38】 Understanding ME? Multimodal Evaluation for Fine-grained Visual Commonsense
标题：理解我吗？面向细粒度视觉常识的多模式评价
链接：https://arxiv.org/abs/2211.05895
作者：Zhecan Wang,Haoxuan You,Yicheng He,Wenhao Li,Kai-Wei Chang,Shih-Fu Chang
机构： Columbia University, New York, University of California, Los Angeles
备注：Accepted to EMNLP 2022 Long Paper
【39】 Employing Graph Representations for Cell-level Characterization of Melanoma MELC Samples
标题：用图形表示法对黑色素瘤黑色素瘤样本进行细胞水平表征
链接：https://arxiv.org/abs/2211.05884
作者：Luis Carlos Rivera Monroy,Leonhard Rist,Martin Eberhardt,Christian Ostalecki,Andreas Baur,Julio Vera,Katharina Breininger,Andreas Maier
机构： Pattern Recognition Lab, Friedrich-Alexander-Universit¨at Erlangen-N¨urnberg, Erlangen, Germany, Department of Dermatology, Universit¨atsklinikum Erlangen, Erlangen, Germany
备注：This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
【40】 Steps towards prompt-based creation of virtual worlds
标题：迈向基于提示的虚拟世界创建的步骤
链接：https://arxiv.org/abs/2211.05875
作者：Jasmine Roberts,Andrzej Banburski-Fahey,Jaron Lanier
机构：UCSD, Microsoft
备注：15 pages
【41】 On the Ramifications of Human Label Uncertainty
标题：关于人类标签不确定性的后果
链接：https://arxiv.org/abs/2211.05871
作者：Chen Zhou,Mohit Prabhushankar,Ghassan AlRegib
【42】 MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis
标题：MIXUP-MIL：多实例学习的新数据增强及甲状腺癌诊断研究
链接：https://arxiv.org/abs/2211.05862
作者：Michael Gadermayr,Lukas Koller,Maximilian Tschuchnig,Lea Maria Stangassinger,Christina Kreutzer,Sebastien Couillard-Despres,Gertie Janneke Oostingh,Anton Hittmair
机构： Salzburg University of Applied Sciences, Department of Information Technology and, Digitalization, Salzburg University of Applied Sciences, Department of Biomedical Sciences, Spinal Cord Injury and Tissue Regeneration Center Salzburg, Research Institute of
【43】 Robust N-1 secure HV Grid Flexibility Estimation for TSO-DSO coordinated Congestion Management with Deep Reinforcement Learning
标题：基于深度强化学习的TSO-DSO协同拥塞管理N-1安全高压电网柔性估计
链接：https://arxiv.org/abs/2211.05855
作者：Zhenqi Wang,Sebastian Wende-von Berg,Martin Braun
机构：University of Kassel, Kassel, Germany, Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), Kassel, Germany
备注：Conference: NEIS 2022, Hamburg
【44】 Test-time adversarial detection and robustness for localizing humans using ultra wide band channel impulse responses
标题：使用超宽带信道脉冲响应定位人类的测试时间敌意检测和稳健性
链接：https://arxiv.org/abs/2211.05854
作者：Abhiram Kolli,Muhammad Jehanzeb Mirza,Horst Possegger,Horst Bischof
机构：Institute of Computer Graphics and Vision, Graz University of Technology, Austria.
备注：5 pages, 4 figures, ICASSP Conference
【45】 Measuring Reliability of Large Language Models through Semantic Consistency
标题：通过语义一致性度量大型语言模型的可靠性
链接：https://arxiv.org/abs/2211.05853
作者：Harsh Raj,Domenic Rosati,Subhabrata Majumdar
机构：Delhi Technological University, Delhi, India, scite.ai, Brooklyn, NY, USA, Trustworthy ML Initiative, Seattle, WA, USA
备注：Accepted and presented in NeurIPS 2022 ML Safety Workshop, this https URL
【46】 The CRINGE Loss: Learning what language not to model
标题：畏缩的损失：学习什么语言不是模型
链接：https://arxiv.org/abs/2211.05826
作者：Leonard Adolphs,Tianyu Gao,Jing Xu,Kurt Shuster,Sainbayar Sukhbaatar,Jason Weston
机构：Meta AI & ETH Zürich, Meta AI & Princeton University
【47】 Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness
标题：随意对话v2：设计大型同意驱动的数据集来衡量算法偏差和健壮性
链接：https://arxiv.org/abs/2211.05809
作者：Caner Hazirbas,Yejin Bang,Tiezheng Yu,Parisa Assar,Bilal Porgali,Vítor Albiero,Stefan Hermanek,Jacqueline Pan,Emily McReynolds,Miranda Bogen,Pascale Fung,Cristian Canton Ferrer
机构： Hong Kong University of Science and Technology
【48】 A quantum neural network with efficient optimization and interpretability
标题：一种具有高效优化和可解释性的量子神经网络
链接：https://arxiv.org/abs/2211.05793
作者：Pei-Lin Zheng,Jia-Bao Wang,Yi Zhang
机构：International Center for Quantum Materials, School of Physics, Peking University, Beijing, China
备注：15 pages, 8 figures
机器翻译由腾讯交互翻译提供，仅供参考
历史文章列表 网站https://www.arxivdaily.com/
注：含中英文摘要速递见公众号【arXiv每日学术速递】,涵盖CS|物理|数学|经济|统计|金融|生物|电气等领域。 |
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发表于 2022-12-8 09:51:22