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Phylourny: efficiently calculating elimination tournament win probabilities via phylogenetic methods
The prediction of knockout tournaments represents an area of large public interest and active academic as well as industrial research. Here, we show...
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Gambling as a Methodological Strategy of Probabilities in University Students
The article aims to analyze how students, when putting statistical knowledge into practice, can formulate problems applied to games of chance that...
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Indistinguishable Predictions and Multi-group Fair Learning
Prediction algorithms assign numbers to individuals that are popularly understood as individual “probabilities”—what is the probability that an...
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Probabilistic Resources Allocation with Group Dependencies in Distributed Computing
In this work, we introduce and study a set of tree-based algorithms for resources allocation considering group dependencies between their parameters....
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Classifier calibration: a survey on how to assess and improve predicted class probabilities
This paper provides both an introduction to and a detailed overview of the principles and practice of classifier calibration. A well-calibrated...
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Allocation of Distributed Resources with Group Dependencies and Availability Uncertainties
In this work, we introduce and study a set of tree-based algorithms for resources allocation considering group dependencies between their parameters....
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A Stratified Fuzzy Group Best Worst Decision-Making Framework
The importance of multi-criteria group decision-making techniques in today’s complex decision-making environment is undeniable. In complex decision...
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Challenges in Cybersecurity Group Interoperability Training
The risk of becoming part of a cyber incident is increasing daily. The gap in skills in human-human, human-computer interaction is one of the biggest...
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Hunting Group Clues with Transformers for Social Group Activity Recognition
This paper presents a novel framework for social group activity recognition. As an expanded task of group activity recognition, social group activity...
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Design and Analysis of Efficient Attention in Transformers for Social Group Activity Recognition
Social group activity recognition is a challenging task extended from group activity recognition, where social groups must be recognized with their...
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Group Fairness in Case-Based Reasoning
There has been a significant recent interest in algorithmic fairness within data-driven systems. In this paper, we consider group fairness within...
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Influence Based Group Recommendation System in Personality and Dynamic Trust
Given the frequent engagement in group activities within daily life, recommending content to a group of users becomes an important task. In...
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Rethinking group activity recognition under the open set condition
In real-world scenarios, the recognition of unknown activities poses a significant challenge for group activity recognition. Existing methods...
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A Novel Classification Method for Group Decision-Making Dimensions
This paper presents a novel and comprehensive classification mechanism that groups numerous dimensions associated with group decision-making...
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CCA Secure Updatable Encryption from Non-mappable Group Actions
Ciphertext-independent updatable encryption (UE) allows to rotate encryption keys and update ciphertexts via a token without the need to first...
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Fairness with censorship and group constraints
Fairness in machine learning (ML) has gained attention within the ML community and the broader society beyond with many fairness definitions and...
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Cost-constrained Group Feature Selection Using Information Theory
A problem of cost-constrained group feature selection in supervised classification is considered. In this setting, the features are grouped and each...
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Assessing Group Fairness with Social Welfare Optimization
Statistical parity metrics have been widely studied and endorsed in the AI community as a means of achieving fairness, but they suffer from at least...
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Probabilities: Bayesian Classifiers
The earliest attempts to predict an example’s class from the knowledge of its attribute values go back to well before World War II—prehistory, by the...
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XsimGCL’s cross-layer for group recommendation using extremely simple graph contrastive learning
Group recommendation involves suggesting items or activities to a group of users based on their collective preferences or characteristics. Graph...
