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人工智能学术速递[2022.12.27]

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发表于 2022-12-28 14:46:58 | 显示全部楼层 |阅读模式
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36篇

【1】 Robust computation of optimal transport by $β$-potential  regularization
标题:基于$β~-位势正则化的最优运输稳健计算
链接:https://arxiv.org/abs/2212.13251
作者:Shintaro Nakamura,Han Bao,Masashi Sugiyama
机构:The University of Tokyo,-,-, Kashiwanoha, Kashiwa City, Chiba ,-, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto ,-, RIKEN AIP center, Nihonbashi ,-chome Mitsui Building,th floor,-,-, Nihonbashi, Chuo-ku, Tokyo ,-, Editors: Emtiyaz Khan and Mehmet Gonen

【2】 Off-Policy Reinforcement Learning with Loss Function Weighted by  Temporal Difference Error
标题:基于时间差分误差加权损失函数的非策略强化学习
链接:https://arxiv.org/abs/2212.13175
作者:Bumgeun Park,Taeyoung Kim,Woohyeon Moon,Luiz Felipe Vecchietti,Dongsoo Har
机构:Cho Chun Shik Graduate School of Mobility, KAIST, Data Science Group, Institute for Basic Science
备注:to be submitted to an AI conference

【3】 Improving Complex Knowledge Base Question Answering via  Question-to-Action and Question-to-Question Alignment
标题:通过问答和问答对齐改进复杂知识库问答
链接:https://arxiv.org/abs/2212.13036
作者:Yechun Tang,Xiaoxia Cheng,Weiming Lu
机构:College of Computer Science and Technology , Zhejiang University

【4】 Unsupervised Representation Learning from Pre-trained Diffusion  Probabilistic Models
标题:基于预训练扩散概率模型的无监督表示学习
链接:https://arxiv.org/abs/2212.12990
作者:Zijian Zhang,Zhou Zhao,Zhijie Lin
机构:Department of Computer Science and Technology, Zhejiang University, Sea AI Lab
备注:Accepted by NeurIPS 2022 Conference

【5】 Refined Edge Usage of Graph Neural Networks for Edge Prediction
标题:图神经网络在边缘预测中的改进边缘使用
链接:https://arxiv.org/abs/2212.12970
作者:Jiarui Jin,Yangkun Wang,Weinan Zhang,Quan Gan,Xiang Song,Yong Yu,Zheng Zhang,David Wipf
机构:Shanghai Jiao Tong University,University of California San Diego,Amazon Web Service
备注:Pre-print

【6】 Neural Shape Compiler: A Unified Framework for Transforming between  Text, Point Cloud, and Program
标题:神经形状编译器:文本、点云和程序之间转换的统一框架
链接:https://arxiv.org/abs/2212.12952
作者:Tiange Luo,Honglak Lee,Justin Johnson
机构:University of Michigan
备注:project page: this https URL

【7】 Human Health Indicator Prediction from Gait Video
标题:基于步态视频的人体健康指标预测
链接:https://arxiv.org/abs/2212.12948
作者:Ziqing Li,Xuexin Yu,Xiaocong Lian,Yifeng Wang,Xiangyang Ji
机构:Tsinghua University, Haidian District, Beijing , China, HIT Campus of University Town of Shenzhen, Shenzhen , China, A R T I C L E I N F O

【8】 Understanding Ethics, Privacy, and Regulations in Smart Video  Surveillance for Public Safety
标题:理解公共安全智能视频监控中的道德、隐私和法规
链接:https://arxiv.org/abs/2212.12936
作者:Babak Rahimi Ardabili,Armin Danesh Pazho,Ghazal Alinezhad Noghre,Christopher Neff,Arun Ravindran,Hamed Tabkhi
机构:University of North Carolina at Charlotte, Charlotte NC , USA

【9】 FMM-Net: neural network architecture based on the Fast Multipole Method
标题:FMM-Net:基于快速多极子方法的神经网络结构
链接:https://arxiv.org/abs/2212.12899
作者:Daria Sushnikova,Pavel Kharyuk,Ivan Oseledets
机构:Skolkovo Institute of Science and Technology, Moscow, Russia

【10】 Closed-form control with spike coding networks
标题:具有尖峰编码网络的闭式控制
链接:https://arxiv.org/abs/2212.12887
作者:Filip S. Slijkhuis,Sander W. Keemink,Pablo Lanillos
机构:∗These authors contributed equally
备注:Under review in an IEEE journal

【11】 QuickNets: Saving Training and Preventing Overconfidence in Early-Exit  Neural Architectures
标题:QuickNets:在早期退出的神经结构中节省训练和防止过度自信
链接:https://arxiv.org/abs/2212.12866
作者:Devdhar Patel,Hava Siegelmann
机构:Biologically Inspired Neural and Dynamical Systems Laboratory (BINDS), College of Computer and Information Sciences, University of Massachusetts Amherst, Amherst, MA , USA
备注:9 pages, 4 figures

【12】 Context-Aware Target Classification with Hybrid Gaussian Process  prediction for Cooperative Vehicle Safety systems
标题:基于混合高斯过程预测的协同车辆安全系统上下文感知目标分类
链接:https://arxiv.org/abs/2212.12819
作者:Rodolfo Valiente,Arash Raftari,Hossein Nourkhiz Mahjoub,Mahdi Razzaghpour,Syed K. Mahmud,Yaser P. Fallah
机构:∗Connected and Autonomous Vehicle Research Lab (CAVREL), Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA, ∗∗Hyundai America Technical Center, Inc. (HATCI), Superior Township, MI, USA

【13】 Towards Long-term Autonomy: A Perspective from Robot Learning
标题:走向长期自主:机器人学习的视角
链接:https://arxiv.org/abs/2212.12798
作者:Zhi Yan,Li Sun,Tomas Krajnik,Tom Duckett,Nicola Bellotto
机构:CIAD UMR , Univ. Bourgogne Franche-Comt´e, UTBM, F-, Belfort, France, Department of Computer Science, University of Sheffield, UK, Czech Technical University, Czechia, Lincoln Centre for Autonomous Systems, University of Lincoln, UK
备注:Accepted by AAAI-23 Bridge Program on AI & Robotics

【14】 Agent-based Modeling and Simulation of Human Muscle For Development of  Software to Analyze the Human Gait
标题:基于智能体的人体肌肉建模与仿真及步态分析软件开发
链接:https://arxiv.org/abs/2212.12760
作者:Sina Saadati,Mohammadreza Razzazi
备注:14 pages, 12 figures

【15】 An optimized fuzzy logic model for proactive maintenance
标题:一种优化的主动维修模糊逻辑模型
链接:https://arxiv.org/abs/2212.12757
作者:Abdelouadoud Kerarmi,Assia Kamal-idrissi,Amal El Fallah Seghrouchni
机构:Seghrouchni, Ai movement, Center of Artificial Intelligence, Mohammed VI Polytechnic, University, Rabat, Morocco, Lip, Sorbonne University, Paris, France
备注:16 pages in single column format, 11 figures, 12th International Conference on Artificial Intelligence, Soft Computing and Applications (AIAA 2022) December 22 ~ 24, 2022, Sydney, Australia

【16】 LMFLOSS: A Hybrid Loss For Imbalanced Medical Image Classification
标题:LMFLOSS:一种非平衡医学图像分类的混合损失
链接:https://arxiv.org/abs/2212.12741
作者:Abu Adnan Sadi,Labib Chowdhury,Nursrat Jahan,Mohammad Newaz Sharif Rafi,Radeya Chowdhury,Faisal Ahamed Khan,Nabeel Mohammed
机构:Nusrat Jahan,  Giga Tech Limited, Dhaka, Bangladesh,  North South University, Dhaka, Bangladesh,  City Hospital, Dhaka, Bangladesh

【17】 Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
标题:用多个预训练模型增强非分布检测
链接:https://arxiv.org/abs/2212.12720
作者:Feng Xue,Zi He,Chuanlong Xie,Falong Tan,Zhenguo Li
机构:Hunan University, Beijing Normal University, Huawei Noah’s Ark Lab

【18】 Stock Market Prediction via Deep Learning Techniques: A Survey
标题:基于深度学习技术的股市预测研究综述
链接:https://arxiv.org/abs/2212.12717
作者:Jinan Zou,Qingying Zhao,Yang Jiao,Haiyao Cao,Yanxi Liu,Qingsen Yan,Ehsan Abbasnejad,Lingqiao Liu,Javen Qinfeng Shi
机构: University of Adelaide,  Northwestern Polytechnical University

【19】 Deep Reinforcement Learning for Heat Pump Control
标题:用于热泵控制的深度强化学习
链接:https://arxiv.org/abs/2212.12716
作者:Tobias Rohrer,Lilli Frison,Lukas Kaupenjohann,Katrin Scharf,Elke Hergenrother
机构:Hergenr¨other,  University of Applied Sciences Darmstadt,  Fraunhofer Institute for Solar Energy Systems

【20】 When Do Curricula Work in Federated Learning?
标题:联合学习中的课程什么时候起作用?
链接:https://arxiv.org/abs/2212.12712
作者:Saeed Vahidian,Sreevatsank Kadaveru,Woonjoon Baek,Weijia Wang,Vyacheslav Kungurtsev,Chen Chen,Mubarak Shah,Bill Lin
机构:University of California San Diego, Czech Technical University,  UCF

【21】 Structure-Enhanced DRL for Optimal Transmission Scheduling
标题:用于优化传输调度的结构增强型DRL
链接:https://arxiv.org/abs/2212.12704
作者:Jiazheng Chen,Wanchun Liu,Daniel E. Quevedo,Saeed R. Khosravirad,Yonghui Li,Branka Vucetic
备注:Paper submitted to IEEE. Copyright may be transferred without notice, after which this version may no longer be accessible. arXiv admin note: substantial text overlap with arXiv:2211.10827

【22】 Real or Fake Text?: Investigating Human Ability to Detect Boundaries  Between Human-Written and Machine-Generated Text
标题:真的还是假的文本?:调查人类识别人类书写和机器生成文本之间的边界的能力
链接:https://arxiv.org/abs/2212.12672
作者:Liam Dugan,Daphne Ippolito,Arun Kirubarajan,Sherry Shi,Chris Callison-Burch
机构:University of Pennsylvania
备注:AAAI 2023 Long Paper. Code is available at this https URL

【23】 On Realization of Intelligent Decision-Making in the Real World: A  Foundation Decision Model Perspective
标题:基于基础决策模型的现实世界智能决策实现研究
链接:https://arxiv.org/abs/2212.12669
作者:Ying Wen,Ziyu Wan,Ming Zhou,Shufang Hou,Zhe Cao,Chenyang Le,Jingxiao Chen,Zheng Tian,Weinan Zhang,Jun Wang
机构:Shanghai Jiao Tong University, Digital Brain Laboratory, ShanghaiTech University, University College London
备注:26 pages, 4 figures

【24】 Hyperspherical Loss-Aware Ternary Quantization
标题:超球面损耗感知三值量化
链接:https://arxiv.org/abs/2212.12649
作者:Dan Liu,Xue Liu
机构:McGill University

【25】 Utilizing Priming to Identify Optimal Class Ordering to Alleviate  Catastrophic Forgetting
标题:利用启动识别最优类别排序来缓解灾难性遗忘
链接:https://arxiv.org/abs/2212.12643
作者:Gabriel Mantione-Holmes,Justin Leo,Jugal Kalita
机构:Department of Computer Science, Lewis & Clark College, Portland, OR, University of Colorado, Colorado Springs, CO
备注:Accepted to IEEE International Conference on Semantic Computing (ICSC) 2023

【26】 Inclusive Artificial Intelligence
标题:包容性人工智能
链接:https://arxiv.org/abs/2212.12633
作者:Dilip Arumugam,Shi Dong,Benjamin Van Roy
机构:Stanford University

【27】 Mantis: Enabling Energy-Efficient Autonomous Mobile Agents with Spiking  Neural Networks
标题:螳螂:使用尖峰神经网络实现能效高的自主移动代理
链接:https://arxiv.org/abs/2212.12620
作者:Rachmad Vidya Wicaksana Putra,Muhammad Shafique
机构:∗Institute of Computer Engineering, Technische Universit¨at Wien (TU Wien), Vienna, Austria, †Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, United Arab Emirates
备注:To appear at the 2023 International Conference on Automation, Robotics and Applications (ICARA), February 2023, Abu Dhabi, UAE. arXiv admin note: text overlap with arXiv:2206.08656

【28】 Continual Causal Abstractions
标题:连续因果抽象
链接:https://arxiv.org/abs/2212.12575
作者:Matej Zečević,Moritz Willig,Jonas Seng,Florian Peter Busch
机构:Florian P. Busch, Computer Science Department, AIML, TU Darmstadt, Germany
备注:Main paper: 2 pages, 1 figure. References: 0.5 page

【29】 Pearl Causal Hierarchy on Image Data: Intricacies & Challenges
标题:图像数据上的珍珠因果层次:复杂性与挑战
链接:https://arxiv.org/abs/2212.12570
作者:Matej Zečević,Moritz Willig,Devendra Singh Dhami,Kristian Kersting
机构:Computer Science Department, TU Darmstadt,Centre for Cognitive Science, TU Darmstadt, Hessian Center for AI (hessian.AI),DFKI
备注:Main paper: 9 pages, References: 2 pages. Main paper: 7 figures

【30】 On How AI Needs to Change to Advance the Science of Drug Discovery
标题:论人工智能如何改变以推进药物发现科学
链接:https://arxiv.org/abs/2212.12560
作者:Kieran Didi,Matej Zečević
机构:Matej Zeˇcevi´c, Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Computer Science Department, TU Darmstadt
备注:Main paper: 6 pages, References: 1.5 pages. Main paper: 3 figures

【31】 A Close Look at Spatial Modeling: From Attention to Convolution
标题:近距离观察空间建模:从关注到卷积
链接:https://arxiv.org/abs/2212.12552
作者:Xu Ma,Huan Wang,Can Qin,Kunpeng Li,Xingchen Zhao,Jie Fu,Yun Fu
机构:†Northeastern University, ‡Meta Reality Labs, ♯Mila

【32】 Kidney and Kidney Tumour Segmentation in CT Images
标题:CT图像中肾和肾肿瘤的分割
链接:https://arxiv.org/abs/2212.13034
作者:Qi Ming How,Hoi Leong Lee
机构:Universiti Malaysia Perlis, Arau, Malaysia

【33】 Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on  Decay Rates and/or Frequencies
标题:对衰减率和/或频率有感应偏差的连续时间非线性动力学建模
链接:https://arxiv.org/abs/2212.13033
作者:Tomoharu Iwata,Yoshinobu Kawahara
机构:NTT Communication Science Laboratories, Kyoto, Japan, Graduate School of Information Science and Technology, Osaka University, Osaka, Japan, Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan

【34】 Detection and Tracking of Low Observable Objects in a Sequence of Image  Frames Using Particle Filter
标题:基于粒子滤波的图像帧序列中低可观测目标的检测与跟踪
链接:https://arxiv.org/abs/2212.13020
作者:Reza Rezaie

【35】 Deep Latent State Space Models for Time-Series Generation
标题:用于时间序列生成的深潜在状态空间模型
链接:https://arxiv.org/abs/2212.12749
作者:Linqi Zhou,Michael Poli,Winnie Xu,Stefano Massaroli,Stefano Ermon
机构:Stanford University, University of Toronto, MILA

【36】 Automated Gadget Discovery in Science
标题:科学中的自动小工具发现
链接:https://arxiv.org/abs/2212.12743
作者:Lea M. Trenkwalder,Andrea López Incera,Hendrik Poulsen Nautrup,Fulvio Flamini,Hans J. Briegel
机构:Institute for Theoretical Physics, University of Innsbruck, Innsbruck, Austria, Department of Philosophy, University of Konstanz, Konstanz, Germany

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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