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Related papers: RPS(1) Preferences

200 papers

Two-sided matching markets have long existed to pair agents in the absence of regulated exchanges. A common example is school choice, where a matching mechanism uses student and school preferences to assign students to schools. In such…

Machine Learning · Computer Science 2021-09-17 Stefania Ionescu , Yuhao Du , Kenneth Joseph , Anikó Hannák

When information acquisition is costly but flexible, a principal may rationally acquire information that favors one group over another. The former group faces incentives to invest in becoming productive, while the latter is discouraged from…

Theoretical Economics · Economics 2024-09-10 Federico Echenique , Anqi Li

Active consumer participation is seen as an integral part of the emerging smart grid. Examples include demand-side management programs, incorporation of consumer-owned energy storage or renewable energy units, and active energy trading.…

Systems and Control · Computer Science 2015-11-10 Walid Saad , Arnold Glass , Narayan Mandayam , H. Vincent Poor

This paper investigates a novel behavioral feature of recursive preferences: aversion to risks that persist over time, or simply \textit{correlation aversion}. Greater persistence provides information about future consumption but reduces…

Theoretical Economics · Economics 2026-03-24 Lorenzo Maria Stanca

This paper develops maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages: we…

Methodology · Statistics 2013-12-03 Le-Yu Chen , Sokbae Lee , Myung Jae Sung

Given an incomplete ratings data over a set of users and items, the preference completion problem aims to estimate a personalized total preference order over a subset of the items. In practical settings, a ranked list of top-$k$ items from…

Social and Information Networks · Computer Science 2019-04-16 Shameem A Puthiya Parambath , Nishant Vijayakumar , Sanjay Chawla

In real-world recommendation systems, users would engage in variety scenarios, such as homepages, search pages, and related recommendation pages. Each of these scenarios would reflect different aspects users focus on. However, the user…

Information Retrieval · Computer Science 2025-06-24 Zhijian Feng , Wenhao Zheng , Xuanji Xiao

Traditional learning approaches for classification implicitly assume that each mistake has the same cost. In many real-world problems though, the utility of a decision depends on the underlying context $x$ and decision $y$. However,…

Machine Learning · Computer Science 2021-04-20 Kush Bhatia , Peter L. Bartlett , Anca D. Dragan , Jacob Steinhardt

Euclidean preferences are a widely studied preference model, in which decision makers and alternatives are embedded in d-dimensional Euclidean space. Decision makers prefer those alternatives closer to them. This model, also known as…

Computer Science and Game Theory · Computer Science 2016-02-29 Dominik Peters

A decision maker's utility depends on her action $a\in A \subset \mathbb{R}^d$ and the payoff relevant state of the world $\theta\in \Theta$. One can define the value of acquiring new information as the difference between the maximum…

Theoretical Economics · Economics 2021-05-04 Farzad Pourbabaee

Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Preference Network (PN) that jointly models various types of domain…

Information Retrieval · Computer Science 2014-07-23 Tran The Truyen , Dinh Q. Phung , Svetha Venkatesh

Decision-making problems often feature uncertainty stemming from heterogeneous and context-dependent human preferences. To address this, we propose a sequential learning-and-optimization pipeline to learn preference distributions and…

Machine Learning · Computer Science 2026-03-19 Benjamin Hudson , Laurent Charlin , Emma Frejinger

This paper focuses on reinforcement learning (RL) with limited prior knowledge. In the domain of swarm robotics for instance, the expert can hardly design a reward function or demonstrate the target behavior, forbidding the use of both…

Machine Learning · Computer Science 2012-08-07 Riad Akrour , Marc Schoenauer , Michèle Sebag

Thermal preferences vary from person to person and may change over time. The main objective of this paper is to sequentially pose intelligent queries to occupants in order to optimally learn the indoor air temperature values which maximize…

Machine Learning · Computer Science 2019-04-02 Nimish Awalgaonkar , Ilias Bilionis , Xiaoqi Liu , Panagiota Karava , Athanasios Tzempelikos

We propose multi-type probabilistic serial (MPS) and multi-type random priority (MRP) as extensions of the well known PS and RP mechanisms to the multi-type resource allocation problem (MTRA) with partial preferences. In our setting, there…

Artificial Intelligence · Computer Science 2020-10-30 Haibin Wang , Sujoy Sikdar , Xiaoxi Guo , Lirong Xia , Yongzhi Cao , Hanpin Wang

We provide an axiomatic foundation for the representation of num\'{e}raire-invariant preferences of economic agents acting in a financial market. In a static environment, the simple axioms turn out to be equivalent to the following choice…

General Finance · Quantitative Finance 2010-11-09 Constantinos Kardaras

Choice modeling has been a central topic in the study of individual preference or utility across many fields including economics, marketing, operations research, and psychology. While the vast majority of the literature on choice models has…

Machine Learning · Statistics 2022-08-22 Zhongze Cai , Hanzhao Wang , Kalyan Talluri , Xiaocheng Li

We develop a theory of quantum rational decision making in the tradition of Anscombe and Aumann's axiomatisation of preferences on horse lotteries. It is essentially the Bayesian decision theory generalised to the space of Hermitian…

Quantum Physics · Physics 2016-12-08 Alessio Benavoli , Alessandro Facchini , Marco Zaffalon

A new general procedure for a priori selection of more predictable events from a time series of observed variable is proposed. The procedure is applicable to time series which contains different types of events that feature significantly…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Igor B. Konovalov

Understanding consumer preferences is essential to product design and predicting market response to these new products. Choice-based conjoint analysis is widely used to model user preferences using their choices in surveys. However,…