Search Results for author: Claudio Silva

Found 8 papers, 4 papers with code

Valuing Player Actions in Counter-Strike: Global Offensive

1 code implementation2 Nov 2020 Peter Xenopoulos, Harish Doraiswamy, Claudio Silva

Esports, despite its expanding interest, lacks fundamental sports analytics resources such as accessible data or proven and reproducible analytical frameworks.

Sports Analytics

TopoMap: A 0-dimensional Homology Preserving Projection of High-Dimensional Data

no code implementations3 Sep 2020 Harish Doraiswamy, Julien Tierny, Paulo J. S. Silva, Luis Gustavo Nonato, Claudio Silva

With very few exceptions, projection techniques are designed to map data from a high-dimensional space to a visual space so as to preserve some dissimilarity (similarity) measure, such as the Euclidean distance for example.

Towards Ground Truth Explainability on Tabular Data

1 code implementation20 Jul 2020 Brian Barr, Ke Xu, Claudio Silva, Enrico Bertini, Robert Reilly, C. Bayan Bruss, Jason D. Wittenbach

In data science, there is a long history of using synthetic data for method development, feature selection and feature engineering.

Feature Engineering Feature Selection

PipelineProfiler: A Visual Analytics Tool for the Exploration of AutoML Pipelines

1 code implementation arXiv 2020 Jorge Piazentin Ono, Sonia Castelo, Roque Lopez, Enrico Bertini, Juliana Freire, Claudio Silva

In recent years, a wide variety of automated machine learning (AutoML) methods have been proposed to search and generate end-to-end learning pipelines.

Human-Computer Interaction

Gradient Dynamics of Shallow Univariate ReLU Networks

no code implementations NeurIPS 2019 Francis Williams, Matthew Trager, Claudio Silva, Daniele Panozzo, Denis Zorin, Joan Bruna

We show that the gradient dynamics of such networks are determined by the gradient flow in a non-redundant parameterization of the network function.

A New Urban Objects Detection Framework Using Weakly Annotated Sets

no code implementations28 Jun 2017 Eric Keiji, Gabriel Ferreira, Claudio Silva, Roberto M. Cesar Jr

The large variety and quantity of data available should be explored but this brings important challenges.

Object Recognition

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