Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Tavares, Anderson R."'
Autor:
Pinto, Rafael C., Tavares, Anderson R.
This paper demonstrates that a single-layer neural network using Parametric Rectified Linear Unit (PReLU) activation can solve the XOR problem, a simple fact that has been overlooked so far. We compare this solution to the multi-layer perceptron (MLP
Externí odkaz:
http://arxiv.org/abs/2409.10821
Autor:
Bazzan, Ana L. C., Tavares, Anderson R., Pereira, André G., Jung, Cláudio R., Scharcanski, Jacob, Carbonera, Joel Luis, Lamb, Luís C., Recamonde-Mendoza, Mariana, da Silveira, Thiago L. T., Moreira, Viviane
The thought-provoking analogy between AI and electricity, made by computer scientist and entrepreneur Andrew Ng, summarizes the deep transformation that recent advances in Artificial Intelligence (AI) have triggered in the world. This chapter present
Externí odkaz:
http://arxiv.org/abs/2310.18324
Publikováno v:
Journal of Applied Logics, IfCoLog Journal of Logics and their Applications, Vol. 10 No. 5 2023
Artificial Intelligence is now recognized as a general-purpose technology with ample impact on human life. This work aims at understanding the evolution of AI and, in particular Machine learning, from the perspective of researchers' contributions to
Externí odkaz:
http://arxiv.org/abs/2205.13131
Recently, the use of sound measures and metrics in Artificial Intelligence has become the subject of interest of academia, government, and industry. Efforts towards measuring different phenomena have gained traction in the AI community, as illustrate
Externí odkaz:
http://arxiv.org/abs/2107.11913
Autor:
Nicolau, Marcio, Tavares, Anderson R., Zhang, Zhiwei, Avelar, Pedro, Flach, João M., Lamb, Luis C., Vardi, Moshe Y.
Computational learning theory states that many classes of boolean formulas are learnable in polynomial time. This paper addresses the understudied subject of how, in practice, such formulas can be learned by deep neural networks. Specifically, we ana
Externí odkaz:
http://arxiv.org/abs/2009.05908
Autor:
Avelar, Pedro H. C., Tavares, Anderson R., da Silveira, Thiago L. T., Jung, Cláudio R., Lamb, Luís C.
This paper presents a methodology for image classification using Graph Neural Network (GNN) models. We transform the input images into region adjacency graphs (RAGs), in which regions are superpixels and edges connect neighboring superpixels. Our exp
Externí odkaz:
http://arxiv.org/abs/2002.05544
In this paper we propose the use of continuous residual modules for graph kernels in Graph Neural Networks. We show how both discrete and continuous residual layers allow for more robust training, being that continuous residual layers are those which
Externí odkaz:
http://arxiv.org/abs/1911.09554
Publikováno v:
Journal of Applied Logics- IfCoLog Journal of Logics & their Applications (FLAP); Nov2023, Vol. 10 Issue 5, p693-817, 125p
Artificial Intelligence is now recognized as a general-purpose technology with ample impact on human life. In this work, we aim to understand the evolution of AI and Machine learning over the years by analyzing researchers' impact, influence, and lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67642d649e4e4ae92cd8901653639379
http://arxiv.org/abs/2205.13131
http://arxiv.org/abs/2205.13131