Scientific workshop "Big Data Analytics"

h1. Seminar "Big Data Analytics"

(sorted by later first)

h2. Schedule 2019, spring

Thursday, 16:20, cab 5212 NSU new building

h3. May, 2019

|23, #|*Munjaradzi Njera* Master thesis

*Andrey Marinov*: Selsam, D., Lamm, M., Bünz, B., Liang, P., de Moura, L., & Dill, D. L. (2018). Learning a SAT solver from single-bit supervision. arXiv preprint arXiv:1802.03685.

~~time slot (25 min)~~

~~time slot (25 min)~~|

|16, #|*Omid Razizadeh* Master Thesis

*Jetina Tsvaki* Master thesis

*Roman Kozinets* Master thesis (imaging)

*Anik Chakrabarthy* Master thesis

*Andrey Marinov* Master thesis: Research on an efficiency of the bilingual model for the silent speech recognition.|

h3. April, 2019

|25, #|*Andray Zubkov* Master thesis

*Evgeniy Kurochkin* Master thesis

*Alexandra Luchkina* Master thesis

*Leyuan Sheng* Master thesis

*Malysheva Anastasia* Master thesis|

|18, #|*Ivan Rogalsky* Open System Categorical Quantum Semantics in NLP (master thesis, review)

*Ravi Kumar* Master thesis

*Jetina Tsvaki* Predicting Oil Movement in a development System Using Deep Latent Dynamic Models

*Dylan Bersans* Outside the closed world: On Using ML for Network Intrusion Detection

*Olga Yakovenko* Course work

*Juan Pinzon* Master thesis|

|11, #|*Leyuan Sheng* Tacotron 2

*Klim Markelov* Master thesis

-*Juan Pinzon* Master thesis-

*Ravi Kumar* State of the art Deep Learning: Evolving Machine Intelligence Toward Tomorrow's

*Malysheva Anastasia* Attention is all you need https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf |

|4, #|*Roman Kozinets* CNN for speech command recognition. Review

-*Ivan Rogalsky* Quantum-Theoretic Approach in Dicstr. Semantics-

*Akilesh Sivaswamy* Master thesis

*Madina Tussupova* Master Thesis

*Madina Tussupova* 5.3. Wieting J., Kiela D. No Training Required: Exploring Random Encoders for Sentence Classification //arXiv preprint arXiv:1901.10444. – 2019. URL (20 min)|

h3. March, 2019

|28, #|-*Ravi Kumar* State of the art Deep Learning: Evolving Machine Intelligence Toward Tomorrow's-

*Munjaradzi Njera* Human-level control through deep reinforcement learning

*Thomas Vialars* Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures

*Petr Gusev* MXNet

*Petr Gusev* Master Thesis|

|21, #2086|*Juan Pinzon* Universal Language Model Fine-tuning for Text Classification

*Elizaveta Tagirova* Master Thesis

-*Petr Gusev* MXNet-

-*Seth Gyamerah* Understanding consumer behavior-|

|14, #2076|*Omid Razizadeh* Pixel Recurrent Neural Networks.

*Klim Markelov* A Style-Based Generator Architecture for Generative Adversarial Networks.

*Anik Chakrabarthy* DisCoCat toy model

*Akilesh Sivaswamy* CosFace|

|7, #2071|-*Andrey Zubkov* Performance of Word Embeddings- (previously reported)

*Alexandra Luchkina* Triplet loss

*Evgeniy Kurochkin* Self-Taught Convolutional Neural Networks for Short Text Clustering

*Olga Yakovenko* BigARTM|

h3. February, 2019

|28, #2058|*Elizaveta Tagirova* Universal Sentence Encoder

*Andrey Zubkov* Neurohackathon on autism disorder: prized solution

~~time slot (25 min)~~

~~time slot (25 min)~~|

|21, #2054|*Vyacheslav Mukhortov* Project Management Practice: teambiudling and project tasks.

*Evgeniy Pavlovskiy* Planning of academic seminar for Spring, 2019|

h2. Schedule 2018, fall

Thursday, 18:10, cab 5273 NSU new building

h3. December, 2018

|6, #2034|*Leyuan Sheng*, CycleGAN

*Tagirova Elizaveta*. LIME (local interpretable model-agnostic explanations) https://arxiv.org/pdf/1602.04938v1.pdf

*Luchkina Alexandra*, Sobolev Training

*Fishman Daniil*, Prediction of enhancer-promoter interactions via natural language processing|

|13, #|*Anton Kolonin*. Topics for master work.

*Evgeniy Averyanov*, Schmidt, Mark. Minimizing finite sums with the stochastic average gradient / M. Schmidt, N. Le Roux, F. Bach // Mathematical Programming. — 2017. — Vol. 162(1). — P. 83–112. — URL: https://link.springer.com/article/10.1007/s10107-016-1030-6

*Polina Potapova*, XNOR-Net, https://arxiv.org/pdf/1603.05279.pdf

*Lee Wonjai*. Bayesian CDF (continue with example)

|

|20, #|-*Artem Sergeev*. ArcFace-

*Gyamerah Seth*, Fuzzy time series on financial forecasting

-*Mulley Loic*, Triplet Loss https://arxiv.org/pdf/1503.03832.pdf-

*Kurochkin Evgeniy*, DenseNet

|

|27, #|*Julien Machet*, Machine learning top down and bottom up.

*Ivan Rogalsky*

*Arsentiy Melnikov* Teacher student curriculum learning https://arxiv.org/pdf/1707.00183.pdf

*Loic Mulley*, Triplet Loss https://arxiv.org/pdf/1503.03832.pdf

*Artem Sergeev*, ArcFace|

h3. November, 2018

|1, #|*Petr Gusev*. ResNet, ResNeXt K. He, X. Zhang, S. Ren, and J. Sun. Deep Residual Learning for Image Recognition. In CVPR, 2016

*Anastasia Malysheva*, Variational Autoencoders

*Anik Chakrabarthy*. Quantum Semantics

~~25 min slot~~|

|8, #|*Akilesh Sivawamy*, Mobile NN.

*Lee Wonjai*. Bayesian CDF

-*Polina Potapova*, XNOR-Net, https://arxiv.org/pdf/1603.05279.pdf- (moved to December)

*Olga Yakovenko*, RNN for Speech Recognition|

|15, #|*Ravi Kumar*, Deep Learning in Mobile and Wireless Networks: a Survey

*Munjaradzi Njera*, Attentioned based LSTM

*Juan Fernando Pinzon Correa*, Rapids AI

*Urynbassarov Mukhtar*, GAN|

|22, #|lost|

|29, #|*Roman Kozinets*, Siamese NN

*Omid Razizadeh*, tSNE

*Jetina Tsvaki*, Natural language based financial forecasting: a survey

*Owen Siyoto*, Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|

h3. October, 2018

|18, #2028|Planning the semester|

|25, #|*Klim Markelov*, Capsule NN

*Andrey Zubkov*, Dynamic Word Embeddings https://arxiv.org/abs/1804.07983

*Vitaly Poteshkin*, MixUp

Planning the semester|

h3. September, 2018

1. 2nd year students coursework pre-defence: (1) #2008, (2) 14.09.2018.

2. Scientific advisors presentations: https://trello.com/b/ZlMTMsS8/bdaai-scientific-topics

# Taylakov D.

# Savostyanov A.N.

# Duchkov A.

# Golovin S.

# Pavlovskiy E.

# Kohanovskiy A.

# Sviridenko D.

# Redyuk A.

# Vityaev E.

h2. [[Archive]]