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Private Data Manipulation in Sponsored Search Auctions

CAAI Artificial Intelligence Research 2023年第1期2卷 114-122页

作者： Xiaotie Deng Tao Lin Tao Xiao Center on Frontiers of Computing Studies Department of Computer SciencePeking UniversityBeijing 100871China School of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02138USA Huawei TCS Lab Shanghai 201206China

The repeated nature of sponsored search auctions allows the seller to implement Myerson’s auction to maximize revenue using past *** since these data are provided by strategic buyers in the auctions,they can be manipulated,which may hurt the seller’s *** model this problem as a Private Data Manipulation(PDM)game:the seller first announces an auction(such as Myerson’s)whose allocation and payment rules depend on the value distributions of buyers;the buyers then submit fake value distributions to the seller to implement the *** seller’s expected revenue and the buyers’expected utilities depend on the auction rule and the game played among the buyers in their choices of the submitted *** the PDM game,we show that Myerson’s auction is equivalent to the generalized first-price auction,and under further assumptions equivalent to the Vickrey-Clarke-Groves(VCG)auction and the generalized second-price *** results partially explain why Myerson’s auction is not as popular as the generalized second-price auction in the practice of sponsored search auctions,and provide new perspectives into data-driven decision making in mechanism design.

关键词： Internet economics sponsored search auction Myerson’s auction generalized first-price auction data-driven decision making

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A preliminary study about gender gap perception in informatics studies in Spain 12

A preliminary study about gender gap perception in informati...

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12th International Conference on Virtual Campus, JICV 2022

作者： Garcia-Holgado, Alicia Gonzalez-Gonzalez, Carina S. Fernandez, Inmaculada Garcia Lopez, Lourdes Moreno Barrenechea, Edurne Rueda, Silvia Navarro, Angeles G. Martinez, Paloma Masia, Belen Navarro, Elena Fornes, Alicia Grial Research Group Universidad DeSalamanca Computer Science and Automation Department Salamanca Spain University of la Laguna Computer Engineering Department San Cristobal de La Laguna Spain Universidad de Málaga Computer Architecture Department Málaga Spain Universidad Carlos Iii de Madrid Computer Science and Engineering Department Madrid Spain Universidad Pública de Navarra Departamento de Estadística Informática y Matemáticas Pamplona Spain Universitat de València Departament of Computer Science Valencia Spain Universidad de Zaragoza Computer Science Department Zaragoza Spain Universidad de Castilla la Mancha Departament of Computing Systems Albacete Spain Computer Vision Center Universitat Autónoma de Barcelona Barcelona Spain

ISBN: (数字)9781665451062

ISBN: (纸本)9781665451062

The gender gap in STEM is an issue that affects regions and countries worldwide. Furthermore, the percentage of women in these areas depends on a range of different factors. In particular, the gender gap is critical in technology in general and, more specifically, in informatics. This problem affects not only the business sector but also society. Informatics is part of our lives;however, 50% of the world population is not represented in the teams that are developing solutions for solving society's problems. In Spain, the number of women with informatics degrees is around 15%. This work describes a case study developed by the committee of Women in Informatics at the Scientific Society of Spanish Informatics (SCIE) to analyse the perception of informatics scientists on the gender gap in informatics. © 2022 IEEE.

关键词： computers

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An Architecture of Adaptive Cognitive Digital Twins for Resilient Healthcare Infrastructures and Services 2nd

An Architecture of Adaptive Cognitive Digital Twins for Re...

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2nd International Workshop on Secure and Resilient Digital Transformation of Healthcare, SUNRISE 2024

作者： Xu, Shouhuai Pirbhulal, Sandeep Abie, Habtamu Department of Computer Science University of Colorado Colorado Springs Colorado SpringsCO80918 United States Norwegian Computing Center/Norsk Regnesentral P.O. Box 114 Blindern OsloN-0314 Norway

ISBN: (纸本)9783031855573

Modern healthcare infrastructures and services are dependent on advanced data analytics, sensing and communication technologies that include 5G/6G networks, Artificial intelligence (AI), Internet of Medical Things (IoMT), Information Technology (IT), and Operational Technology (OT). This integration incurs a large vulnerability surface and cyber attackers can exploit those vulnerabilities to wage successful attacks against modern healthcare infrastructures and services. Therefore, identifying potential vulnerabilities in healthcare infrastructures and services and securing end-to-end monitoring of sensitive healthcare infrastructures and services are crucial for achieving resilient healthcare infrastructures and services. In this paper, we propose an architecture designed to enhance the resilience of healthcare infrastructures and services. This architecture is centered around the concept of Adaptive Cognitive Digital Twins (ACDTs), which are capable of orchestrating adaptive defenses to proactively respond to anticipated cyber attacks. Our architecture has seven layers. We detail the functions at each layer of the architecture to guide the design and development of mechanisms that can be employed at each layer. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 5G mobile communication systems

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MetaCity: Data-driven sustainable development of complex cities

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The Innovation 2025年第2期6卷 88-103,87页

作者： Yunke Zhang Yuming Lin Guanjie Zheng Yu Liu Nicholas Sukiennik Fengli Xu Yongjun Xu Feng Lu Qi Wang Yuan Lai Li Tian Nan Li Dongping Fang Fei Wang Tao Zhou Yong Li Yu Zheng Zhiqiang Wu Huadong Guo Department of Electronic Engineering Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084China John Hopcroft Center for Computer Science Shanghai Jiao Tong UniversityShanghai 200240China University of Chinese Academy of Sciences Beijing 100049China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China Department of Civil and Environmental Engineering Northeastern UniversityBostonMA 02115USA School of Architecture Tsinghua UniversityBeijing 100084China School of Civil Engineering Tsinghua UniversityBeijing 100084China Big Data Research Center University of Electronic Science and Technology of ChinaChengdu 611731China JD iCity JD Technology&JD Intelligent Cities ResearchBeijing 100176China College of Architecture and Urban Planning Tongji UniversityShanghai 200292China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China These authors contributed equally

Cities are complex systems that develop under complicated interactions among their human and environmental *** generates substantial outcomes and opportunities while raising challenges including congestion,air pollution,inequality,etc.,calling for efficient and reasonable solutions to sustainable ***,booming technologies generate large-scale data of complex cities,providing a chance to propose data-driven solutions for sustainable urban *** paper provides a comprehensive overview of data-driven urban sustainability *** this review article,we conceptualize MetaCity,a general framework for optimizing resource usage and allocation problems in complex cities with data-driven *** this framework,we decompose specific urban sustainable goals,e.g.,efficiency and resilience,review practical urban problems under these goals,and explore the probability of using data-driven technologies as potential solutions to the challenge of *** the basis of extensive urban data,we integrate urban problem discovery,operation of urban systems simulation,and complex decision-making problem solving into an entire cohesive framework to achieve sustainable development goals by optimizing resource allocation problems in complex cities.

关键词： resource usage sustainable development urbanization resilience data driven urban systems simulation complex cities complexity

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Estimation of Hamiltonian Parameters from Thermal States

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Physical Review Letters 2024年第4期133卷 040802-040802页

作者： Luis Pedro García-Pintos Kishor Bharti Jacob Bringewatt Hossein Dehghani Adam Ehrenberg Nicole Yunger Halpern Alexey V. Gorshkov Theoretical Division (T4) Joint Center for Quantum Information and Computer Science and Joint Quantum Institute Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) 1 Fusionopolis Way # 16-16 Connexis Singapore 138632 Republic of Singapore Department of Physics Institute for Physical Science and Technology

We upper bound and lower bound the optimal precision with which one can estimate an unknown Hamiltonian parameter via measurements of Gibbs thermal states with a known temperature. The bounds depend on the uncertainty in the Hamiltonian term that contains the parameter and on the term’s degree of noncommutativity with the full Hamiltonian: higher uncertainty and commuting operators lead to better precision. We apply the bounds to show that there exist entangled thermal states such that the parameter can be estimated with an error that decreases faster than 1/n, beating the standard quantum limit. This result governs Hamiltonians where an unknown scalar parameter (e.g., a component of a magnetic field) is coupled locally and identically to n qubit sensors. In the high-temperature regime, our bounds allow for pinpointing the optimal estimation error, up to a constant prefactor. Our bounds generalize to joint estimations of multiple parameters. In this setting, we recover the high-temperature sample scaling derived previously via techniques based on quantum state discrimination and coding theory. In an application, we show that noncommuting conserved quantities hinder the estimation of chemical potentials.

关键词： Quantum metrology Quantum parameter estimation Quantum sensing

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Quantum-Informed Recursive Optimization Algorithms

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PRX Quantum 2024年第2期5卷 020327-020327页

作者： Jernej Rudi Finžgar Aron Kerschbaumer Martin J.A. Schuetz Christian B. Mendl Helmut G. Katzgraber BMW AG Munich Germany Department of Computer Science Technical University Munich School of CIT Garching Germany Amazon Quantum Solutions Lab Seattle Washington USA AWS Center for Quantum Computing Pasadena California USA Technical University of Munich Institute for Advanced Study Garching Germany

We propose and implement a family of quantum-informed recursive optimization (QIRO) algorithms for combinatorial optimization problems. Our approach leverages quantum resources to obtain information that is used in problem-specific classical reduction steps that recursively simplify the problem. These reduction steps address the limitations of the quantum component (e.g., locality) and ensure solution feasibility in constrained optimization problems. Additionally, we use backtracking techniques to further improve the performance of the algorithm without increasing the requirements on the quantum hardware. We showcase the capabilities of our approach by informing QIRO with correlations from classical simulations of shallow circuits of the quantum approximate optimization algorithm, solving instances of maximum independent set and maximum satisfiability problems with hundreds of variables. We also demonstrate how QIRO can be deployed on a neutral atom quantum processor to find large independent sets of graphs. In summary, our scheme achieves results comparable to classical heuristics even with relatively weak quantum resources. Furthermore, enhancing the quality of these quantum resources improves the performance of the algorithms. Notably, the modular nature of QIRO offers various avenues for modifications, positioning our work as a template for a broader class of hybrid quantum-classical algorithms for combinatorial optimization.

关键词： Adiabatic quantum optimization Optimization problems Quantum algorithms Quantum information with atoms & light

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Towards Context-aware Support for Color Vision Deficiency: An Approach Integrating LLM and AR

Towards Context-aware Support for Color Vision Deficiency: A...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Shogo Morita Yan Zhang Takuto Yamauchi Sinan Chen Jialong Li Kenji Tei School of Computing Tokyo Institute of Technology Tokyo Japan International Research Center for Neurointelligence University of Tokyo Tokyo Japan Department of Computer Science and Engineering Waseda University Tokyo Japan Center of Mathematical and Data Sciences Kobe University Kobe Japan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

People with color vision deficiency often face challenges in distinguishing colors such as red and green, which can complicate daily tasks and require the use of assistive tools or environmental adjustments. Current support tools mainly focus on presentation-based aids, like the color vision modes found in iPhone accessibility settings. However, offering context-aware support, like indicating the doneness of meat, remains a challenge since task-specific solutions are not cost-effective for all possible scenarios. To address this, our paper proposes an application that provides contextual and autonomous assistance. This application is mainly composed of: (i) an augmented reality interface that efficiently captures context; and (ii) a multi-modal large language model-based reasoner that serves to cognitize the context and then reason about the appropriate support contents. Preliminary user experiments with two color vision deficient users across five different scenarios have demonstrated the effectiveness and universality of our application.

关键词： Green products Color Faces Consumer electronics Augmented reality Context modeling

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Towards Context-aware Support for Color Vision Deficiency: An Approach Integrating LLM and AR

arXiv

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arXiv 2024年

作者： Morita, Shogo Zhang, Yan Yamauchi, Takuto Chen, Sinan Li, Jialong Tei, Kenji School of Computing Tokyo Institute of Technology Tokyo Japan International Research Center for Neurointelligence the University of Tokyo Tokyo Japan Department of Computer Science and Engineering Waseda University Tokyo Japan Center of Mathematical and Data Sciences Kobe University Kobe Japan

People with color vision deficiency often face challenges in distinguishing colors such as red and green, which can complicate daily tasks and require the use of assistive tools or environmental adjustments. Current support tools mainly focus on presentation-based aids, like the color vision modes found in iPhone accessibility settings. However, offering context-aware support, like indicating the doneness of meat, remains a challenge since task-specific solutions are not cost-effective for all possible scenarios. To address this, our paper proposes an application that provides contextual and autonomous assistance. This application is mainly composed of: (i) an augmented reality interface that efficiently captures context;and (ii) a multi-modal large language model-based reasoner that serves to cognitize the context and then reason about the appropriate support contents. Preliminary user experiments with two color vision deficient users across five different scenarios have demonstrated the effectiveness and universality of our application. © 2024, CC BY.

关键词： Color

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Memory-Augmented Transformer for Efficient End-to-End Video Grounding

Memory-Augmented Transformer for Efficient End-to-End Video ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Yuanwu Xu Mohan Chen Yuejie Zhang Rui Feng Tao Zhang Shang Gao School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University School of Information Management and Engineering Shanghai Key Laboratory of Financial Information Technology Shanghai University of Finance and Economics School of Information Technology Deakin University

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Video grounding aims to localize a specific segment corresponding to a text query in an untrimmed video. Due to the tremendous computational cost required to process the video frames, the de facto paradigm of video grounding is to extract video features using pretrained video encoders. The parameters of the video encoders are fixed during training, which limits the performance of the localization model. To solve this problem, we propose a Memory-Augmented Transformer (MAT) model. Specifically, each video is split into non-overlapping clips, and our MAT processes videos in a clip-by-clip manner while caching video features into FIFO cached memory queues. By enabling early return, our MAT outperforms previous methods with only less than 60% frames seen. Extensive experimental results on three public benchmark datasets demonstrate that our MAT can achieve competitive performance while being much more efficient than currently prevailing two-stage methods. Code is available at https://***/xuyw1997/MAT.

关键词： Training Location awareness Codes Grounding Computational modeling Streaming media Predictive models

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Characterizing the Evolution of Size and Inheritance in Object-Oriented Software 20

Characterizing the Evolution of Size and Inheritance in Obje...

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20th Brazilian Symposium on Software Quality, SBQS 2021

作者： Sousa, Bruno Luan De Bigonha, Mariza Andrade Da Silva Ferreira, Kecia Aline Marques Franco, Glaura Da Conceição Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte Minas Gerais Brazil Department of Computing Federal Center for Technological Education of Minas Gerais Belo Horizonte Minas Gerais Brazil Department of Statistics Universidade Federal de Minas Gerais Belo Horizonte Minas Gerais Brazil

ISBN: (纸本)9781450395533

Software evolution consists of adapting, correcting, and updating a system. It is widely known that the systems became increasingly complex and challenging to be maintained over their evolution. However, the way the systems' internal structure evolves is not known in detail. Understanding how the internal software structure evolves is essential to help developers better plan, manage, and perform software maintenance tasks. In this work, we present an empirical analysis to investigate how the internal structure of object-oriented systems evolves from the perspective of inheritance hierarchy and size. Besides, we analyzed the set of classes within the systems that affect these dimensions' evolution and how such classes evolve. We used a methodology based on time series, linear regression techniques, and trend tests to analyze the evolution of object-oriented systems. Using this methodology, we identified the function that better explains how the size and the inheritance tree evolve. This study revealed eight software evolution properties, among them: inheritance hierarchy tends to increase in depth and decrease in breadth;inheritance hierarchy depth and the size of classes grow according to a linear model. The empirical evidence found in this work provides a fine-grained knowledge of how object-oriented software systems' internal structure evolves from internal dimensions. © 2021 ACM.

关键词： Time series

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