Kyle Deeds and Ziniu Wu
September 13, 2023
The Case for Cardinality Bounds: Principled Conservatism in Query Optimization
Introduction In the last decade, the database community has identified cardinality estimation as the primary stumbling block for modern query optimizers. Cardinality estimates, which estimate the size of sub-plan queries, are the primary basis for choosing between query plans, so poor estimates may result in catastrophic query execution plans. Research on this topic has consistently […]
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Dimitris Sacharins - Giorgos Giannopoulos - Loukas Kavouras
June 19, 2024
Auditing bias of recourse in classifiers (part I)
Introduction Fairness is a fundamental principle reflecting our innate sense of justice and equity. The essence of fairness lies in the equitable, unbiased and just treatment of all individuals. Nevertheless, translating this principle to specific rules, people, and systems can adhere to is highly context specific, with context meaning, social and cultural circumstances, as well […]
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Mohamed Sharaf
February 16, 2023
Utilizing the Synergy between Query Refinement and View Recommendation for Visual Data Exploration
In this blog, we discuss the potential benefits of augmenting automated view recommendation solutions with query refinement techniques towards achieving insightful data exploration. Particularly, effective data exploration has been fueled by many approaches that rely on either view recommendation or query refinement, as two separate and independent techniques for gaining valuable insights from data. In […]
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Boris Glavic
January 24, 2023
Why Uncertainty is Unavoidable and What We Can Do About That
Uncertainty arises naturally in many application domains due to measurement errors, human error in data entry or transformation, missing data and bias in data collection, and many other reasons. When uncertainty is ignored during data preprocessing and analysis, this leads to hard to trace errors which can have severe real world implications such as false incarcerations […]
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karimaechihabi
December 29, 2022
Similarity Search for Scalable Data Science: The Past, Present and Exciting Road Ahead
Similarity search is a fundamental building block for a myriad of critical data science applications involving large collections of high-dimensional objects, including data discovery, data cleaning, information retrieval, classification, outlier detection and clustering. Similarity search finds objects in a collection close to a given query according to some definition of sameness. This challenging problem has […]
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