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Computational pricing in Internet era

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Frontiers of Computer Science 2018年第1期12卷 40-54页

作者： Fei TIAN Tao QIN Tie-Yan LIU microsoft research asia Beijing 100080 China

Pricing plays a central rule to a company＇s prof- itability, and therefore has been extensively studied in the literature of economics. When designing a pricing mech- anism/model, an important principle to consider is ＂price discrimination＂, which refers to selling the same resources with different prices according to different values of buy- ers. To meet the ＂price discrimination＂ principle, especially when the number of buyers is large, computational methods, which act in a more accurate and principled way, are usu- ally needed to determine the optimal allocation of sellers＇ re- sources （whom to sell to） and the optimal payment of buyers （what to charge）. Nowadays, in the Internet era in which quite a lot of buy and sell processes are conducted through Internet, the design of computational pricing models faces both new challenges and opportunities, considering that （i） nearly real- time interactions between people enable the buyers to reveal their needs and enable the sellers to expose their information in a more expressive manner, （ii） the large-scale interaction data require powerful methods for more efficient processing and enable the sellers to model different buyers in a more precise manner. In this paper, we review recent advances on the analysis and design of computational pricing models for representative Internet industries, e.g., online advertising and cloud computing. In particular, we introduce how computa- tional approaches can be used to analyze buyer＇s behaviors （i.e., equilibrium analysis）, improve resource utilization （i.e., social welfare analysis）, and boost seller＇s profit （i.e., revenue analysis）. We also discuss how machine learning techniques can be used to better understand buyer＇s behaviors and design more effective pricing mechanisms, given the availability oflarge scale data. Moreover, we make discussions on future re- search directions on computational pricing, which hopefully can inspire more researchers to contribute to this important

关键词： computational pricing price discrimination on-line advertising cloud computing mechanism design

A Survey of visual Analytics Techniques and Applications: State-of-the-Art research and Future Challenges

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Journal of Computer Science & Technology 2013年第5期28卷 852-867页

作者：孙国道巫英才梁荣华刘世霞 Internet Graphics group Microsoft Research Asia College of Information Engineering Zhejiang University of Technology

visual analytics employs interactive visualizations to integrate users＇ knowledge and inference capability into numerical/algorithmic data analysis processes. It is an active research field that has applications in many sectors, such as security, finance, and business. The growing popularity of visual analytics in recent years creates the need for a broad survey that reviews and assesses the recent developments in the field. This report reviews and classifies recent work into a set of application categories including space and time, multivariate, text, graph and network, and other applications. More importantly, this report presents analytics space, inspired by design space, which relates each application category to the key steps in visual analytics, including visual mapping, model-based analysis, and user interactions. We explore and discuss the analytics space to acld the current understanding and better understand research trends in the field.

关键词： visual analytics information visualization data analysis user interaction

Worst-Case Nash Equilibria in Restricted Routing

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Journal of Computer Science & Technology 2012年第4期27卷 710-717页

作者：陆品燕余昌远 microsoft research asia ACM Baidu.Inc

We study the network routing problem with restricted and related links. There are parallel links with possibly different speeds, between a source and a sink. Also there are users, and each user has a traffic of some weight to assign to one of the links from a subset of all the links, named his/her allowable set. The users choosing the same link suffer the same delay, which is equal to the total weight assigned to that link over its speed. A state of the system is called a Nash equilibrium if no user can decrease his/her delay by unilaterally changing his/her link. To measure the performance degradation of the system due to the selfish behavior of all the users, Koutsoupias and Papadimitriou proposed the notion Price of Anarchy （denoted by PoA）, which is the ratio of the maximum delay in the worst-case Nash equilibrium and in an optimal solution. The PoA for this restricted related model has been studied, and a linear lower bound was obtained. However in their bad instance, some users can only use extremely slow links. This is a little artificial and unlikely to appear in a real world. So in order to better understand this model, we introduce a parameter for the system, and prove a better Price of Anarchy in terms of the parameter. We also show an important application of our result in coordination mechanism design for task scheduling game. We propose a new coordination mechanism, group-Makespan, for unrelated selfish task scheduling game with improved price of anarchy.

关键词： routing Nash equilibria price of anarchy

Follow the perturbed approximate leader for solving semi-bandit combinatorial optimization

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Frontiers of Computer Science 2021年第5期15卷 161-172页

作者： Feidiao YANG Wei CHEN Jialin ZHANG Xiaoming SUN Institute of computing Technology Chinese Academy of SciencesBejing 100190China University of Chinese Academy of Sciences Beijing 100190China microsoft research asia Beijing 100080China

Combinatorial optimization in the face of uncertainty is a challenge in both operational research and machine *** this paper,we consider a special and important class called the adversarial online combinatorial optimization with semi-bandit feedback,in which a player makes combinatorial decisions and gets the corresponding feedback *** existing algorithms focus on the regret guarantee or assume there exists an efficient offline oracle,it is still a challenge to solve this problem efficiently if the offline counterpart is *** this paper,we propose a variant of the Follow-the-Perturbed-Leader(FPL)algorithm to solve this *** the existing FPL approach,our method employs an approximation algorithm as an offline oracle and perturbs the collected data by adding nonnegative random *** ap-proach is simple and computationally ***,it can guarantee a sublinear(1+ε)-scaled regret of order O(T^(2/3))for any smallε>0 for an important class of combinatorial optimization problems that admit an FPTAS(fully polynomial time approximation scheme),in which T is the number of rounds of the learning *** addition to the theoretical analysis,we also conduct a series of experiments to demonstrate the performance of our algorithm.

关键词： online learning online combinatorial optimization semi-bandit follow-the-perturbed-leader

When Factorization Meets Heterogeneous Latent Topics： An Interpretable Cross-Site Recommendation Framework

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Journal of Computer Science & Technology 2015年第4期30卷 917-932页

作者：辛欣林钦佑魏骁驰黄河燕 Beijing Engineering research Center of High Volume Language Information Processing & Cloud computing School of Computer Science Beijing Institute of Technology Beijing 100081 China microsoft research asia Beijing 100080 China

Data sparsity is a well-known challenge in recommender systems. Previous studies alleviate this problem by incorporating the information within the corresponding social media site. In this paper, we solve this challenge by exploring cross-site information. Specifically, we examine： 1） how to effectively and efficiently utilize cross-site ratings and content features to improve recommendation performance and 2） how to make the recommendation interpretable by utilizing content features. We propose a joint model of matrix factorization and latent topic analysis. Heterogeneous content features are modeled by multiple kinds of latent topics. In addition, the combination of matrix factorization and latent topics makes the recommendation result interpretable. Therefore, the above two issues are simultaneously solved. Through a real-world ***, where user behaviors in three social media sites are collected, we demonstrate that the proposed model is effective in improving recommendation performance and interpreting the rationale of ratings.

关键词： collaborative filtering recommender system topic analysis

Cross-layer optimization in ultra wideband networks

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Science in China(Series F) 2007年第5期50卷 760-770页

作者： WU Qi BI JingPing GUO ZiHua XIONG YongQiang ZHANG Qian LI ZhongCheng Institute of computing Technology Chinese Academy of Sciences Beijing 100080 China microsoft research asia Beijing 100080 China Lab of Network Science Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

Ultra wideband （UWB） network brings both chance and challenge to personal area wireless communications. Compared with other IEEE 802 small range wireless protocols （such as WLAN and Bluetooth）, UWB has both extremely high bandwidth （up to 480 Mbpa） and low radiation. Moreover, the structured MAC layer of UWB is the fundamental difference to WLAN. The top one is that only when two UWB devices belong to the same piconet can they communicate with each other directly, which means that we must jointly consider topology formation and routing when deploying UWB networks because the interaction between routing and topology formation makes separate optimization ineffective. This paper tries to optimize UWB network from a cross-layer point of view. Specifically, given device spatial distribution and traffic requirement, we want to form piconets and determine routing jointly, to maximize the overall throughput. We formulate the problem of joint optimization to mixed-integer programming and give a practical lower bound that is very close to the theoretical upper bound in our simulation. Furthermore, our lower bound is much better than an algorithm that only considers topology formation in UWB networks.

关键词： ultra wideband medium access control cross-layer design topology formation piconet

XGCN:a library for large-scale graph neural network recommendations

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Frontiers of Computer Science 2024年第3期18卷 247-249页

作者： Xiran SONG Hong HUANG Jianxun LIAN Hai JIN National Engineering research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China microsoft research asia Beijing 100080China

1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing ***,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.

关键词： scaling gained operations

Dynamic properties of fuzzy Petri net model and related analysis

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Journal of Central South University 2015年第12期22卷 4717-4723页

作者：周恺卿 Azlan Mohd Zain 莫礼平 Soft computing research group Faculty of ComputingUniversiti Teknologi Malaysia UTM Skudai College of Information Science and Engineering Jishou University

Fuzzy Petri net(FPN) has been extensively applied in industrial fields for knowledge-based systems or systems with *** the applications of FPN are known to be successful,the theoretical research of FPN is still at an initial *** pave a way for further study,this work explores related dynamic properties of FPN including reachability,boundedness,safeness,liveness and *** whole methodology is divided into two *** the first phase,a comparison between elementary net system(EN_system) and FPN is established to prove that the FPN is an extensive formalism of Petri nets using a backwards-compatible extension ***,current research results of dynamic properties are utilized to analyze FPN *** results illustrate that FPN model is bounded,safe,weak live and fair,and can support theoretical evidences for designing related decomposition algorithm.

关键词： fuzzy Petri net elementary net system backwards-compatible extension method dynamic properties

Competitive Cloud Pricing for Long-Term Revenue Maximization

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Journal of Computer Science & Technology 2019年第3期34卷 645-656页

作者： Jiang Rong Tao Qin Bo An Institute of computing Technology Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China microsoft research asia Beijing 100080China School of Computer Science and Engineering Nanyarig Technological UniversitySingapore 639798Singapore

We study the pricing policy optimization problem for cloud providers while considering three properties of the real-world market:1)providers have only incomplete information about the market;2)it is in evolution due to the increasing number of users and decreasing marginal cost of providers:3)it is fully competitive because of providers'and users'revenuedriven *** far as we know,there is no existing work investigating the optimal pricing policies under such realistic *** first propose a comprehensive model for the real-world cloud inarket and formulatc it as a stochastic *** we use the Markov perfect equilibrium(MPE)to describe providers5 optimal *** we decompose the problem of computing the MPE into two subtasks:1)dividing the stochastic game into many normal-formal games and calculating their Nash equilibria,for which we develop an algorithm ensuring to converge,and 2)computing the MPE of the original game,which is efficiently solved by an algorithm combining the Nash equilibria based on a mild *** results show that our algorithms are efficient for computing MPE and the MPE strategy leads to much higher profits for providers compared with existing policies.

关键词： cloud computing Markov perfect equilibrium game theory revenue maximization