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Object Detection: A Review In this article, I review some 2D Object Detection papers. R-CNN R-CNN (Girshick et al., 2014) (Regions with CNN features) presents a first, preliminary, approach to Object Detection. Figure 1: R-CNN Pipeline: Extract... [Read More]

I’m really proud to announce that “The Reinforcement Learning Workshop” is finally published! Packt Interactive Amazon Starting with... [Read More]

I attented the course Regularization Methods for Machine Learning (RegML 2020). Topics: Regularization Methods: Penalization, Projection, Early Stopping. Kernel Methods Regularization in Multi-Task Learning Sparsity Geometric Deep Learning Representation Learning Here you can find my notes about the lessons. There can be errors, imprecisions and so... [Read More]

I went through the last Facebook paper (Carion et al., 2020), which proposes a new architecture, DETR, for object detection and segmentation based on Transformers. To better understand the paper, I decided to review the basic principles of Transformers and Attention. I am not pretending to write the... [Read More]

.PDF Web Version Here I share a brief summary of the theory behind Machine Learning. These notes were taken during my M.Sc. (2016/2017) following the Machine Learning lectures. They might contain errors, they can be imprecise,... [Read More]