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There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order instances given feedback in the form of preference judgments, i.e., statements to the effect…

Machine Learning · Computer Science 2011-05-30 W. W. Cohen , R. E. Schapire , Y. Singer

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola

People regularly share items using online social media. However, people's decisions around sharing---who shares what to whom and why---are not well understood. We present a user study involving 87 pairs of Facebook users to understand how…

Human-Computer Interaction · Computer Science 2014-12-04 Amit Sharma , Dan Cosley

Learning of preference models from human feedback has been central to recent advances in artificial intelligence. Motivated by the cost of obtaining high-quality human annotations, we study efficient human preference elicitation for…

Machine Learning · Computer Science 2026-02-17 Subhojyoti Mukherjee , Anusha Lalitha , Kousha Kalantari , Aniket Deshmukh , Ge Liu , Yifei Ma , Branislav Kveton

Recommender systems attempts to identify and recommend the most preferable item (product-service) to an individual user. These systems predict user interest in items based on related items, users, and the interactions between items and…

Machine Learning · Computer Science 2021-04-07 Atousa Zarindast , Jonathan Wood , Anuj Sharma

We consider a setting where $n$ buyers, with combinatorial preferences over $m$ items, and a seller, running a priority-based allocation mechanism, repeatedly interact. Our goal, from observing limited information about the results of these…

Computer Science and Game Theory · Computer Science 2014-08-29 Avrim Blum , Yishay Mansour , Jamie Morgenstern

We introduce a new kind of Information Theory. From a finite number of local, noisy comparisons, we want to design a robust filter such that the outcome is a high ranking number, Both analytical and numerical results are encouraging and we…

Disordered Systems and Neural Networks · Physics 2009-11-07 A. Capocci , F. Slanina , Y. -C. Zhang

We consider the problem of learning from revealed preferences in an online setting. In our framework, each period a consumer buys an optimal bundle of goods from a merchant according to her (linear) utility function and current prices,…

Data Structures and Algorithms · Computer Science 2014-12-02 Kareem Amin , Rachel Cummings , Lili Dworkin , Michael Kearns , Aaron Roth

Package-to-group recommender systems recommend a set of unified items to a group of people. Different from conventional settings, it is not easy to measure the utility of group recommendations because it involves more than one user. In…

Information Retrieval · Computer Science 2021-12-30 Ryoma Sato

The selection process of proposals is a crucial component of scientific progress and innovations. Limited resources must be allocated in the most effective way to maximise advancements and the production of new knowledge, especially as it…

Physics and Society · Physics 2015-04-22 Antonio Navarra

Recommender systems have become increasingly important with the rise of the web as a medium for electronic and business transactions. One of the key drivers of this technology is the ease with which users can provide feedback about their…

Information Retrieval · Computer Science 2024-11-05 Dong Li

In 2010, Web users ordered, only in Amazon, 73 items per second and massively contribute reviews about their consuming experience. As the Web matures and becomes social and participatory, collaborative filters are the basic complement in…

Information Retrieval · Computer Science 2011-12-13 Vafopoulos Michalis , Oikonomou Michael

Verifying software correctness has always been an important and complicated task. Recently, formal proofs of critical properties of algorithms and even implementations are becoming practical. Currently, the most powerful automated proof…

Logic in Computer Science · Computer Science 2019-04-10 Michael Raskin , Christoph Welzel

It is well known that options can make planning more efficient, among their many benefits. Thus far, algorithms for autonomously discovering a set of useful options were heuristic. Naturally, a principled way of finding a set of useful…

Machine Learning · Computer Science 2018-02-01 Roy Fox , Michal Moshkovitz , Naftali Tishby

Lotteries are commonly employed in school choice to fairly resolve priority ties; however, current practices typically keep students uninformed about their lottery outcomes at the time of preference submission. This paper advocates for…

Theoretical Economics · Economics 2025-12-04 Lingbo Huang , Jun Zhang

This paper introduces a new comparison base stable sorting algorithm, named RS sort. RS Sort involves only the comparison of pair of elements in an array which ultimately sorts the array and does not involve the comparison of each element…

Data Structures and Algorithms · Computer Science 2014-07-23 Harsh Ranjan , Sumit Agarwal , Niraj Kumar Singh

With the prevalence of e-commence websites and the ease of online shopping, consumers are embracing huge amounts of various options in products. Undeniably, shopping is one of the most essential activities in our society and studying…

Computer Vision and Pattern Recognition · Computer Science 2017-02-23 Kuan-Ting Chen , Jiebo Luo

How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on products and services which…

Information Retrieval · Computer Science 2014-03-14 Md. Ansarul Haque

In this paper an interesting application of mathematics in economics is presented: the formulation of the theory of consumer basic problem, grounded on the concept of preferences relation and operationalized with optimization tools.

Optimization and Control · Mathematics 2021-11-10 Manuel Alberto M. Ferreira , José António Filipe

We consider an assortment selection and pricing problem in which a seller has $N$ different items available for sale. In each round, the seller observes a $d$-dimensional contextual preference information vector for the user, and offers to…

Machine Learning · Computer Science 2025-03-18 Yigit Efe Erginbas , Thomas A. Courtade , Kannan Ramchandran
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