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Related papers: A Cardinal Comparison of Experts

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Automated decision support systems promise to help human experts solve multiclass classification tasks more efficiently and accurately. However, existing systems typically require experts to understand when to cede agency to the system or…

Machine Learning · Computer Science 2023-07-03 Eleni Straitouri , Lequn Wang , Nastaran Okati , Manuel Gomez Rodriguez

In this paper, we experimentally compare major approval-based multiwinner voting rules. To this end, we define a measure of similarity between two equal-sized committees subject to a given election. Using synthetic elections coming from…

Computer Science and Game Theory · Computer Science 2024-01-23 Piotr Faliszewski , Martin Lackner , Krzysztof Sornat , Stanisław Szufa

We investigate the problem of a principal looking to contract an expert to provide a probability forecast for a categorical event. We assume all experts have a common public prior on the event's probability, but can form more accurate…

Computer Science and Game Theory · Computer Science 2014-04-30 Mark Braverman , Gal Oshri

Effective human-AI collaboration requires a system design that provides humans with meaningful ways to make sense of and critically evaluate algorithmic recommendations. In this paper, we propose a way to augment human-AI collaboration by…

Machine Learning · Computer Science 2022-05-03 Maria De-Arteaga , Alexandra Chouldechova , Artur Dubrawski

Controlled experiments (A/B tests or randomized field experiments) are the de facto standard to make data-driven decisions when implementing changes and observing customer responses. The methodology to analyze such experiments should be…

Applications · Statistics 2020-03-06 Shafi Kamalbasha , Manuel J. A. Eugster

There has been increasing interest in recent years in the development of approaches to estimate causal effects when the number of potential confounders is prohibitively large. This growth in interest has led to a number of potential…

Methodology · Statistics 2020-02-05 Joseph Antonelli , Matthew Cefalu

Agents' judgment depends on perception and previous knowledge. Assuming that previous knowledge depends on perception, we can say that judgment depends on perception. So, if judgment depends on perception, can agents judge that they have…

Neurons and Cognition · Quantitative Biology 2012-02-21 Ahmed M. Mahran

We study how to perform tests on samples of pairs of observations and predictions in order to assess whether or not the predictions are prudent. Prudence requires that that the mean of the difference of the observation-prediction pairs can…

Risk Management · Quantitative Finance 2022-10-03 Dirk Tasche

If we assume the axiom of choice, then every two cardinal numbers are comparable. In the absence of the axiom of choice, this is no longer so. For a few cardinalities related to an arbitrary infinite set, we will give all the possible…

Logic · Mathematics 2007-05-23 Lorenz Halbeisen , Saharon Shelah

Automated decision support systems that are able to infer second opinions from experts can potentially facilitate a more efficient allocation of resources; they can help decide when and from whom to seek a second opinion. In this paper, we…

Machine Learning · Computer Science 2022-07-01 Nina L. Corvelo Benz , Manuel Gomez Rodriguez

In this paper peer review reliability is investigated based on peer ratings of research teams at two Belgian universities. It is found that outcomes can be substantially influenced by the different ways in which experts attribute ratings.…

Digital Libraries · Computer Science 2013-07-29 Nadine Rons , Eric Spruyt

We present the problem of finding comparable researchers for any given researcher. This problem has many motivations. Firstly, know thyself. The answers of where we stand among research community and who we are most alike may not be easily…

Digital Libraries · Computer Science 2014-07-08 Graham Cormode , S. Muthukrishnan , Jinyun Yan

In this paper, paired comparison models with stochastic background are investigated. We focus on the models that allow three options for choice. We estimate all parameters, the strength of the objects and the boundaries of equal decision,…

Optimization and Control · Mathematics 2025-02-20 László Gyarmati , Csaba Mihálykó , Eva Orbán-Mihálykó , András Mihálykó

In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of experts. In contrast to the NormalHedge bound, which mainly…

Machine Learning · Computer Science 2015-03-17 Alexey Chernov , Vladimir Vovk

Bayesian experts who are exposed to different evidence often make contradictory probabilistic forecasts. An aggregator, ignorant of the underlying model, uses this to calculate her own forecast. We use the notions of scoring rules and…

Economics · Quantitative Finance 2018-02-13 Itai Areili , Yakov Babichenko , Rann Smorodinsky

Conformal prediction is a statistically rigorous method for quantifying uncertainty in models by having them output sets of predictions, with larger sets indicating more uncertainty. However, prediction sets are not inherently actionable;…

Machine Learning · Computer Science 2025-02-17 Jesse C. Cresswell , Bhargava Kumar , Yi Sui , Mouloud Belbahri

In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of experts. In contrast to the Normal- Hedge bound, which mainly…

Machine Learning · Computer Science 2014-08-12 Alexey Chernov , Vladimir Vovk

Comparing alternatives in pairs is a very well known technique of ranking creation. The answer to how reliable and trustworthy ranking is depends on the inconsistency of the data from which it was created. There are many indices used for…

Discrete Mathematics · Computer Science 2020-01-28 Konrad Kułakowski , Dawid Talaga

In 1975, G. P\'olya suggested that if two proofreaders found $a$ and $b$ errors in a text, of which $c$ errors were found by both of them, then a reasonable approximation of the unknown number $e$ of all errors is $e\approx ab/c$. We…

Probability · Mathematics 2026-01-27 Martin Klazar

Consider a predictor who ranks eventualities on the basis of past cases: for instance a search engine ranking webpages given past searches. Resampling past cases leads to different rankings and the extraction of deeper information. Yet a…

Theoretical Economics · Economics 2021-03-04 Patrick H. O'Callaghan