English
Related papers

Related papers: Ordinal Lindahl Equilibrium for Voting

200 papers

Reinforcement learning has significantly enhanced the reasoning capabilities of Large Language Models (LLMs) in complex problem-solving tasks. Recently, the introduction of DeepSeek R1 has inspired a surge of interest in leveraging…

Machine Learning · Computer Science 2025-08-07 Jinghang Han , Jiawei Chen , Hang Shao , Hao Ma , Mingcheng Li , Xintian Shen , Lihao Zheng , Wei Chen , Tao Wei , Lihua Zhang

We revisit the problem of online learning with individual fairness, where an online learner strives to maximize predictive accuracy while ensuring that similar individuals are treated similarly. We first extend the frameworks of Gillen et…

Machine Learning · Computer Science 2024-03-12 Yahav Bechavod

We study the problem of fair $k$-committee selection under an egalitarian objective. Given $n$ agents partitioned into $m$ groups (\eg, demographic quotas), the goal is to aggregate their preferences to form a committee of size $k$ that…

Data Structures and Algorithms · Computer Science 2026-01-01 Ameet Gadekar , Aristides Gionis , Suhas Thejaswi , Sijing Tu

We present a polynomial-time algorithm for computing an optimal committee of size $k$ under any given Thiele voting rule for elections on the Voter Interval domain (i.e., when voters can be ordered so that each candidate is approved by a…

Computer Science and Game Theory · Computer Science 2026-04-08 Pasin Manurangsi , Krzysztof Sornat

Regression is a fundamental tool in scientific research. Ordinary least squares (OLS), one of the most widely used regression methods, enjoys several desirable properties, including the best linear unbiased estimator (BLUE) property. It is…

Methodology · Statistics 2026-05-29 Hwiyoung Lee , Shuo Chen

We study the problem of coalitional manipulation---where $k$ manipulators try to manipulate an election on $m$ candidates---under general scoring rules, with a focus on the Borda protocol. We do so both in the weighted and unweighted…

Data Structures and Algorithms · Computer Science 2017-08-17 Orgad Keller , Avinatan Hassidim , Noam Hazon

A hybrid quantum-classical algorithm is a computational scheme in which quantum circuits are used to extract information that is then processed by a classical routine to guide subsequent quantum operations. These algorithms are especially…

Quantum Physics · Physics 2025-09-03 Alon Levi , Ziv Ossi , Eliahu Cohen , Amit Te'eni

Iterative preference optimization methods have recently been shown to perform well for general instruction tuning tasks, but typically make little improvement on reasoning tasks (Yuan et al., 2024, Chen et al., 2024). In this work we…

Computation and Language · Computer Science 2024-06-27 Richard Yuanzhe Pang , Weizhe Yuan , Kyunghyun Cho , He He , Sainbayar Sukhbaatar , Jason Weston

Fairness in clustering has been considered extensively in the past; however, the trade-off between the two objectives -- e.g., can we sacrifice just a little in the quality of the clustering to significantly increase fairness, or…

Machine Learning · Computer Science 2024-08-20 Rashida Hakim , Ana-Andreea Stoica , Christos H. Papadimitriou , Mihalis Yannakakis

In content-oblivious computation, n nodes wish to compute a given task over an asynchronous network that suffers from an extremely harsh type of noise, which corrupts the content of all messages across all channels. In a recent work,…

Data Structures and Algorithms · Computer Science 2024-05-07 Fabian Frei , Ran Gelles , Ahmed Ghazy , Alexandre Nolin

We consider the problem of funding public goods that are complementary in nature. Examples include charities handling different needs (e.g., protecting animals vs. providing healthcare), charitable donations to different individuals, or…

Theoretical Economics · Economics 2025-10-14 Felix Brandt , Matthias Greger , Erel Segal-Halevi , Warut Suksompong

This paper considers a dynamic game with transferable utilities (TU), where the characteristic function is a continuous-time bounded mean ergodic process. A central planner interacts continuously over time with the players by choosing the…

Computer Science and Game Theory · Computer Science 2012-04-24 Dario Bauso , Puduru Viswanadha Reddy , Tamer Basar

Many societal decision problems lie in high-dimensional continuous spaces not amenable to the voting techniques common for their discrete or single-dimensional counterparts. These problems are typically discretized before running an…

Multiagent Systems · Computer Science 2018-10-30 Nikhil Garg , Vijay Kamble , Ashish Goel , David Marn , Kamesh Munagala

Motivated by the difficulty of specifying complete ordinal preferences over a large set of $m$ candidates, we study voting rules that are computable by querying voters about $t < m$ candidates. Generalizing prior works that focused on…

Computer Science and Game Theory · Computer Science 2024-09-30 Daniel Halpern , Safwan Hossain , Jamie Tucker-Foltz

Eigenoptions (EOs) have been recently introduced as a promising idea for generating a diverse set of options through the graph Laplacian, having been shown to allow efficient exploration. Despite its initial promising results, a couple of…

Artificial Intelligence · Computer Science 2017-12-13 Miao Liu , Marlos C. Machado , Gerald Tesauro , Murray Campbell

Shortlisting of candidates--selecting a group of "best" candidates--is a special case of multiwinner elections. We provide the first in-depth study of the computational complexity of strategic voting for shortlisting based on the perhaps…

Multiagent Systems · Computer Science 2019-08-15 Robert Bredereck , Andrzej Kaczmarczyk , Rolf Niedermeier

Learning relational tabular data has gained significant attention recently, but most studies focus on single tables, overlooking the potential of cross-table learning. Cross-table learning, especially in scenarios where tables lack shared…

Machine Learning · Computer Science 2025-02-17 Zhaomin Wu , Shida Wang , Ziyang Wang , Bingsheng He

Bayesian optimization (BO) has emerged during the last few years as an effective approach to optimizing black-box functions where direct queries of the objective are expensive. In this paper we consider the case where direct access to the…

Machine Learning · Statistics 2017-04-13 Javier Gonzalez , Zhenwen Dai , Andreas Damianou , Neil D. Lawrence

Organizations are often unable to align the interests of all stakeholders with the financial success of the organization (e.g. due to regulation). However, continuous organizations (COs) introduce a paradigm shift. COs offer immediate…

Optimization and Control · Mathematics 2022-03-22 Howard Heaton , Sam Green

We introduce ORPO-Distill, a general-purpose method for cross-architecture LLM distillation that formulates the problem as a preference optimization task. Unlike standard CoT distillation, the approach transfers knowledge through diverse…

Machine Learning · Computer Science 2025-09-30 Aasheesh Singh , Vishal Vaddina , Dagnachew Birru
‹ Prev 1 8 9 10 Next ›