Scientific workshop "Big Data Analytics"

25 minutes for one presentation.
Each student has to present a research.

Opened list of cutting-edge topics:
* ResNet, ResNeXt - *Petr Gusev* - K. He, X. Zhang, S. Ren, and J. Sun. Deep Residual Learning
for Image Recognition. In CVPR, 2016
* "Dynamic Word Embeddings":https://arxiv.org/abs/1804.07983 - *Andrey Zubkov*
* "Capsule NN" - *Klim Markelov*, paper: https://arxiv.org/pdf/1710.09829, presentation: https://cedar.buffalo.edu/~srihari/CSE676/9.12%20CapsuleNets.pdf
* "MixUp":https://arxiv.org/pdf/1710.09412.pdf - *Vitaly Poteshkin* ("AdaMixUp":https://arxiv.org/pdf/1809.02499.pdf in addition)
* Variational Autoencoders - *Anastasia Malysheva*
* ArcFace -
* UMAP - McInnes, Leland and John Healy (2018). “UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction”. In: ArXiv e-prints. arXiv: "1802.03426 [stat.ML]":http://arxiv.org/abs/1802.03426
* Siamese NN -
* Quantum Semantics -
* MobileNN
* Triplet Loss
* "Sobolev Training":https://arxiv.org/pdf/1706.04859
* "Rapids AI":http://rapids.ai/ -