35 citations · 57 across the 10 of their papers we have counts for
10 papers
Mediation Challenges and Socio-Technical Gaps for Explainable Deep Learning Applications
Rafael Brandão, Joel Carbonera, Clarisse de Souza +3
The presumed data owners' right to explanations brought about by the General Data Protection Regulation in Europe has shed light on the social challenges of explainable artificial…
Modeling Epistemological Principles for Bias Mitigation in AI Systems: An Illustration in Hiring Decisions
Marisa Vasconcelos, Carlos Cardonha, Bernardo Gonçalves
Artificial Intelligence (AI) has been used extensively in automatic decision making in a broad variety of scenarios, ranging from credit ratings for loans to recommendations of mov…
Show me the material evidence: Initial experiments on evaluating hypotheses from user-generated multimedia data
Bernardo Gonçalves
Subjective questions such as `does neymar dive', or `is clinton lying', or `is trump a fascist', are popular queries to web search engines, as can be seen by autocompletion suggest…
Bsmooth: Learning from user feedback to disambiguate query terms in interactive data retrieval
Bernardo Gonçalves, H. V. Jagadish
There is great interest in supporting imprecise queries (e.g., keyword search or natural language queries) over databases today. To support such queries, the database system is typ…
A note on the complexity of the causal ordering problem
Bernardo Gonçalves, Fabio Porto
In this note we provide a concise report on the complexity of the causal ordering problem, originally introduced by Simon to reason about causal dependencies implicit in systems of…
Managing large-scale scientific hypotheses as uncertain and probabilistic data
Bernardo Gonçalves
In view of the paradigm shift that makes science ever more data-driven, in this thesis we propose a synthesis method for encoding and managing large-scale deterministic scientific…
-DB: A system for data-driven hypothesis management and analytics
Bernardo Gonçalves, Frederico C. Silva, Fabio Porto
The vision of -DB introduces deterministic scientific hypotheses as a kind of uncertain and probabilistic data, and opens some key technical challenges for enabling data-driven…
Design-theoretic encoding of deterministic hypotheses as constraints and correlations into U-relational databases
Bernardo Gonçalves, Fabio Porto
In view of the paradigm shift that makes science ever more data-driven, in this paper we consider deterministic scientific hypotheses as uncertain data. In the form of mathematical…
-DB: Managing scientific hypotheses as uncertain data
Bernardo Gonçalves, Fabio Porto
In view of the paradigm shift that makes science ever more data-driven, we consider deterministic scientific hypotheses as uncertain data. This vision comprises a probabilistic dat…
Managing large-scale scientific hypotheses as uncertain and probabilistic data with support for predictive analytics
Bernardo Gonçalves, Fabio Porto
The sheer scale of high-resolution raw data generated by simulation has motivated non-conventional approaches for data exploration referred as `immersive' and `in situ' query proce…