121 citations · 125 across the 13 of their papers we have counts for
7 papers · 1 filter
From Textual Columns to Query Plans: A Unified Relational-Semantic Execution Framework for Hybrid Query Processing
Nima Shahbazi, Seiji Maekawa, Nikita Bhutani +1
Real-world table question answering often involves hybrid schemas in which some query-relevant information is explicit in relational columns, while other attributes, predicates, or…
Weighted Set Multi-Cover on Bounded Universe and Applications in Package Recommendation
Nima Shahbazi, Aryan Esmailpour, Stavros Sintos
The weighted set multi-cover problem is a fundamental generalization of set cover that arises in data-driven applications where one must select a small, low-cost subset from a larg…
FairEM360: A Suite for Responsible Entity Matching
Nima Shahbazi, Mahdi Erfanian, Abolfazl Asudeh +2
Entity matching is one the earliest tasks that occur in the big data pipeline and is alarmingly exposed to unintentional biases that affect the quality of data. Identifying and mit…
Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching
Nima Shahbazi, Nikola Danevski, Fatemeh Nargesian +2
Entity matching (EM) is a challenging problem studied by different communities for over half a century. Algorithmic fairness has also become a timely topic to address machine bias…
Data Coverage for Detecting Representation Bias in Image Datasets: A Crowdsourcing Approach
Melika Mousavi, Nima Shahbazi, Abolfazl Asudeh
Existing machine learning models have proven to fail when it comes to their performance for minority groups, mainly due to biases in data. In particular, datasets, especially socia…
Reliability Evaluation of Individual Predictions: A Data-centric Approach
Nima Shahbazi, Abolfazl Asudeh
Machine learning models only provide probabilistic guarantees on the expected loss of random samples from the distribution represented by their training data. As a result, a model…
Representation Bias in Data: A Survey on Identification and Resolution Techniques
Nima Shahbazi, Yin Lin, Abolfazl Asudeh +1
Data-driven algorithms are only as good as the data they work with, while data sets, especially social data, often fail to represent minorities adequately. Representation Bias in d…