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Related papers: Utility Elicitation as a Classification Problem

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Budget aggregation is a process in which citizens vote by declaring their individual ideal budget allocation, and a pre-determined rule aggregates all votes into a single outcome. Recent theoretical work has proposed various aggregation…

Computer Science and Game Theory · Computer Science 2026-04-14 Ayelet Amster , Lioz Akirav , Rica Gonen , Erel Segal-Halevi

App store-inspired elicitation is the practice of exploring competitors' apps, to get inspiration for requirements. This activity is common among developers, but little insight is available on its practical use, advantages, and possible…

Software Engineering · Computer Science 2023-01-31 Alessio Ferrari , Paola Spoletini

Selecting techniques is a crucial element of the business analysis approach planning in IT projects. Particular attention is paid to the choice of techniques for requirements elicitation. One of the promising methods for selecting…

Software Engineering · Computer Science 2023-08-22 Denys Gobov , Olga Solovei

Preference elicitation explicitly asks users what kind of recommendations they would like to receive. It is a popular technique for conversational recommender systems to deal with cold-starts. Previous work has studied selection bias in…

Information Retrieval · Computer Science 2024-05-02 Shashank Gupta , Harrie Oosterhuis , Maarten de Rijke

Most of existing studies on submodular maximization focus on selecting a subset of items that maximizes a \emph{single} submodular function. However, in many real-world scenarios, we might have multiple user-specific functions, each of…

Machine Learning · Computer Science 2024-09-06 Jing Yuan , Shaojie Tang

In the face of uncertainty, the need for probabilistic assessments has long been recognized in the literature on forecasting. In classification, however, comparative evaluation of classifiers often focuses on predictions specifying a single…

Methodology · Statistics 2023-05-31 Johannes Resin

Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative…

Artificial Intelligence · Computer Science 2009-11-10 Ali E. Abbas

We propose an easy-to-use methodology to allocate one of the groups which have been previously built from a complete learning data base, to new individuals. The learning data base contains continuous and categorical variables for each…

Statistics Theory · Mathematics 2016-08-14 Patrick Letrémy , Marie Cottrell , Eric Esposito , Valérie Laffite , Sally Showk

The ultimate goal of any software developer seeking a competitive edge is to meet stakeholders needs and expectations. To achieve this, it is necessary to effectively and accurately manage stakeholders system requirements. The paper…

Software Engineering · Computer Science 2018-03-19 Anupama Prasanth , Sandhia Valsala , Safeeullah Soomro

In the theory of social choice the research is focused around the projection of individual preference orders to the social preference order. Also, the justification of the preference order formalism begins with the concept of utility i.e.…

Computer Science and Game Theory · Computer Science 2010-10-27 Redjan F. Shabani

Eliciting the preferences of a set of agents over a set of alternatives is a problem of fundamental importance in social choice theory. Prior work on this problem has studied the query complexity of preference elicitation for the…

Computer Science and Game Theory · Computer Science 2016-04-19 Palash Dey , Neeldhara Misra

Random utility theory models an agent's preferences on alternatives by drawing a real-valued score on each alternative (typically independently) from a parameterized distribution, and then ranking the alternatives according to scores. A…

Multiagent Systems · Computer Science 2012-11-13 Hossein Azari Soufiani , David C. Parkes , Lirong Xia

Prediction in a small-sized sample with a large number of covariates, the "small n, large p" problem, is challenging. This setting is encountered in multiple applications, such as precision medicine, where obtaining additional samples can…

Artificial Intelligence · Computer Science 2017-07-14 Pedram Daee , Tomi Peltola , Marta Soare , Samuel Kaski

Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating together preferences of multiple agents. We study here the…

Artificial Intelligence · Computer Science 2012-04-18 Toby Walsh

[Context and motivation:] For realistic self-adaptive systems, multiple quality attributes need to be considered and traded off against each other. These quality attributes are commonly encoded in a utility function, for instance, a…

Software Engineering · Computer Science 2021-03-19 Rebekka Wohlrab , David Garlan

In cases of uncertainty, a multi-class classifier preferably returns a set of candidate classes instead of predicting a single class label with little guarantee. More precisely, the classifier should strive for an optimal balance between…

Machine Learning · Computer Science 2020-05-28 Thomas Mortier , Marek Wydmuch , Krzysztof Dembczyński , Eyke Hüllermeier , Willem Waegeman

The unit selection problem is to identify a group of individuals who are most likely to exhibit a desired mode of behavior, for example, selecting individuals who would respond one way if incentivized and a different way if not. The unit…

Artificial Intelligence · Computer Science 2022-10-18 Ang Li , Song Jiang , Yizhou Sun , Judea Pearl

The sum-utility maximization problem is known to be important in the energy systems literature. The conventional assumption to address this problem is that the utility is concave. But for some key applications, such an assumption is not…

Computer Science and Game Theory · Computer Science 2021-12-07 Chao Zhang , Samson Lasaulce , Li Wang , Lucas Saludjian , H. Vincent Poor

Different from shopping at retail stores, consumers on e-commerce platforms usually cannot touch or try products before purchasing, which means that they have to make decisions when they are uncertain about the outcome (e.g., satisfaction…

Information Retrieval · Computer Science 2020-08-20 Zhichao Xu , Yi Han , Yongfeng Zhang , Qingyao Ai

The main goal of this topic is to showcase several studied algorithms for estimating the linear utility function to predict the users preferences. For example, if a user comes to buy a car that has several attributes including speed, color,…

Information Retrieval · Computer Science 2025-06-17 Thomas Hoang