Demo Data from VLDB 2026 / reviewers in the wild / expert
Igor Braga
dblp:137/4943
· DBLP profile ↗
4ranked-venue papers
3as first author
0since 2021 · last 2020
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorDatabases, data management, data science and information retrieval · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Data mining · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data mining › statistical analysis › statistical estimation
density ratio estimation |
0.2 | 1 | 2015 | Stochastic Density Ratio Estimation and Its Application to Feature Selection · IJCAI 2015 |
Data mining › dimensionality reduction
feature selection |
0.2 | 1 | 2015 | Stochastic Density Ratio Estimation and Its Application to Feature Selection · IJCAI 2015 |
Methods — techniques the papers use, named apart from their topics
feature selection · 0.2density ratio estimation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Does the Lean Inception Methodology Contribute to the Software Project Initiation Phase?
Igor Braga, Marcelo Nogueira, Nuno Santos 0002, Ricardo J. Machado 0001 |
ICCSA (6) | 1 |
| 2015 | Stochastic Density Ratio Estimation and Its Application to Feature Selection
Igor Braga |
IJCAI | 1 |
| 2015 | Improving the kernel regularized least squares method for small-sample regression
Igor Braga, Maria Carolina Monard |
Neurocomputing | 1 |
| 2014 | A Constructive Setting for the Problem of Density Ratio EstimationabstractWe introduce a constructive setting for the problem of density ratio estimation through the solution of a multidimensional integral equation. In this equation, not only its right hand side is approximately known, but also the integral operator is approximately defined. We show that this ill-posed problem has a rigorous solution and obtain the solution in a closed form. The key element of this solution is the novel V-matrix, which captures the geometry of the observed samples. We compare our method with previously proposed ones, using both synthetic and real data. Our experimental results demonstrate the good potential of the new approach. Vladimir Vapnik, Igor Braga, Rauf Izmailov |
SDM | 2 |