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Related papers: Planning with Partial Preference Models

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In this paper we consider the collaborative ranking setting: a pool of users each provides a small number of pairwise preferences between $d$ possible items; from these we need to predict preferences of the users for items they have not yet…

Machine Learning · Statistics 2015-07-17 Dohyung Park , Joe Neeman , Jin Zhang , Sujay Sanghavi , Inderjit S. Dhillon

We propose a novel and efficient algorithm for the collaborative preference completion problem, which involves jointly estimating individualized rankings for a set of entities over a shared set of items, based on a limited number of…

Machine Learning · Statistics 2016-11-16 Suriya Gunasekar , Oluwasanmi Koyejo , Joydeep Ghosh

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

The large majority of inferences drawn in empirical political research follow from model-based associations (e.g. regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim…

Methodology · Statistics 2016-12-20 Skyler J. Cranmer , Bruce A. Desmarais

In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profile. We argue that the step that follows, i.e, determining…

Machine Learning · Computer Science 2018-02-22 Luisa M Zintgraf , Diederik M Roijers , Sjoerd Linders , Catholijn M Jonker , Ann Nowé

A structure called a decision making problem is considered. The set of outcomes (consequences) is partially ordered according to the decision maker's preferences. The problem is how these preferences affect a decision maker to prefer one of…

Category Theory · Mathematics 2007-05-23 Victor V. Rozen , Grigori Zhitomirski

This paper investigates simultaneous preference and metric learning from a crowd of respondents. A set of items represented by $d$-dimensional feature vectors and paired comparisons of the form ``item $i$ is preferable to item $j$'' made by…

Machine Learning · Statistics 2022-07-11 Gregory Canal , Blake Mason , Ramya Korlakai Vinayak , Robert Nowak

The paper concerns the probabilistic evaluation of plans in the presence of unmeasured variables, each plan consisting of several concurrent or sequential actions. We establish a graphical criterion for recognizing when the effects of a…

Artificial Intelligence · Computer Science 2013-02-21 Judea Pearl , James M. Robins

Similarity join, which can find similar objects (e.g., products, names, addresses) across different sources, is powerful in dealing with variety in big data, especially web data. Threshold-driven similarity join, which has been extensively…

Databases · Computer Science 2017-07-13 Chuancong Gao , Jiannan Wang , Jian Pei , Rui Li , Yi Chang

The shift from private vehicles to public and shared transport is crucial to reducing emissions and meeting climate targets. Consequently, there is an urgent need to develop a multimodal transport trip planning approach that integrates…

Optimization and Control · Mathematics 2025-02-21 Yimeng Zhang , Oded Cats , Shadi Sharif Azadeh

The recent increase in the volume of online meetings necessitates automated tools for managing and organizing the material, especially when an attendee has missed the discussion and needs assistance in quickly exploring it. In this work, we…

Computation and Language · Computer Science 2023-04-28 Negar Arabzadeh , Ali Ahmadvand , Julia Kiseleva , Yang Liu , Ahmed Hassan Awadallah , Ming Zhong , Milad Shokouhi

In this paper we extend the principle of proportional representation to rankings. We consider the setting where alternatives need to be ranked based on approval preferences. In this setting, proportional representation requires that…

Computer Science and Game Theory · Computer Science 2016-12-06 Piotr Skowron , Martin Lackner , Markus Brill , Dominik Peters , Edith Elkind

As large language models (LLMs) become integral to intelligent user interfaces (IUIs), their role as decision-making agents raises critical concerns about alignment. Although extensive research has addressed issues such as factuality, bias,…

Artificial Intelligence · Computer Science 2025-04-23 Anna Karnysheva , Christian Drescher , Dietrich Klakow

Diverse planning is the problem of finding multiple plans for a given problem specification, which is at the core of many real-world applications. For example, diverse planning is a critical piece for the efficiency of plan recognition…

Artificial Intelligence · Computer Science 2023-10-04 Mustafa F. Abdelwahed , Joan Espasa , Alice Toniolo , Ian P. Gent

Engineering design problems are often modeled as multi-objective optimization tasks in which a scalarized utility function selects an optimal design from the Pareto set. In practice, preferences are imperfectly known, so uncertainty in the…

Applications · Statistics 2026-05-01 Chia-Ruei Liu , Yongjia Song , Qiong Zhang , Cameron Turner

In many applications, human and LLM evaluators use assessments of relevant criteria to create an overall evaluation for an item or individual. For example, in admissions, committees assess candidates on attributes such as test scores, GPA,…

Machine Learning · Computer Science 2026-05-19 Madeline Celi Kitch , Nihar B. Shah

On the basis of an analysis of previous research, we present a generalized approach for measuring the difference of plans with an exemplary application to machine scheduling. Our work is motivated by the need for such measures, which are…

Artificial Intelligence · Computer Science 2015-03-17 Martin Josef Geiger

The ability to generate multiple plans is central to using planning in real-life applications. Top-quality planners generate sets of such top-cost plans, allowing flexibility in determining equivalent ones. In terms of the order between…

Artificial Intelligence · Computer Science 2024-04-03 Michael Katz , Junkyu Lee , Jungkoo Kang , Shirin Sohrabi

The notion of preferences plays an important role in many disciplines including service robotics which is concerned with scenarios in which robots interact with humans. These interactions can be favored by robots taking human preferences…

In planning problems, it is often challenging to fully model the desired specifications. In particular, in human-robot interaction, such difficulty may arise due to human's preferences that are either private or complex to model.…

Robotics · Computer Science 2021-01-01 Mahsa Ghasemi , Evan Scope Crafts , Bo Zhao , Ufuk Topcu