Scientific workshop "Big Data Analytics"

h1. Seminar "Big Data Analytics"

(sorted by later first)

h2. Schedule 2020, spring

Thursday, 16:20, -cab 0207 NSU new building, '-1' elevator floor-, online: https://zoom.us/j/910812617

h3. May, 2020

|7, #|*Ravi Kumar* Master

*Owen Siyoto* Master

*Owen Siyoto* Learning to interpret satellite images in global scale using wikipedia

*Oladotun Aluko* Coursework

*Alexander Rusnak* Coursework

*Vladislav Panferov* Coursework

*Abhishek Saxena* Blockchain for AI: Review and open research challenges

|14, #|*Kaivalya Pandey* Coursework

*Andrey Yashkin* Coursework

*Rohan Rathore* Coursework

*Sergey Garmaev* Coursework

*Dinesh Reddy* Coursework

*Elena Voskoboy* Coursework|

|21, #|*Alexey Korolev* Coursework

*Mohamed Nasser* End-to-End 3D Face Reconstruction with Deep Neural Networks

*Vlaidslav Panferov* You Only Look Once: Unified, Real-Time Object Detection

*Alexander Donets* Coursework

*Daria Pirozhkova* Coursework

*Rishabh Tiwari* Coursework|

|28, #|*Alix Bernard* Coursework

*Mukul Vishwas* Coursework

*Watana Pongsapas* Coursework

*Raphael Blankson* Coursework

*Abhishek Saxena* Coursework

*Nikita Nikolaev* Coursework|

h3. April, 2020

|2, #|[Optional] Daia Scientist - values of a professional|

|9 -2-, #|*Thibault Kollen* Flipout: Efficient pseudo-independent weight perturbations on mini-batches

*Richard Fambon* Tensor Networks

*Alexander Rusnak* GPT-2

*Dinesh Reddy* Brain Tumor Sementation Using Deep Learning by Type Specific Sorting of Images

*Alix Bernard* Deep Learning based Approach to Reduced Order Modelling

*Ravi Kumar* Complex Convolution. IEEE

*Olga Yakovenko* University of Pau|

|16 -9-, #|*Rohan Rathore* Layer-wise relevance propagation: an overview

*Antoine Logeais* Weight uncertainty in neural networks

-*Owen Siyoto* Learning to interpret satellite images in global scale using wikipedia-

*Alexey Korolev* Bert-dst: Scalable end-to-end dialogue state tracking with bidirectional encoder representations from transformer

*Alexander Donets* Implicit weight uncertainty in neural networks|

|23 -16-, #|*Jetina Tsvaki* Understanding mixup training methods

*Jetina Tsvaki* Master

*Mukul Vishwas* A Study on Face Recognition Techniques with Age and Gender Classification

*Rishabh Tiwari*

*Geoffroy de Felcourt* Jasper: An end-to-end convolutional neural acoustic model

*Fishman Daniil* XGBoost: A Scalable Tree Boosting System

*Fishman Daniil* Master

-*Mikhail Rodin* Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization-|

|30, #|*Raphael Blankson* Towards quantum machine learning with tensor networks 

*Vassily Baranov* Coursework

*Kalmutskiy Kirill* Coursework

*Mikhail Liz* Coursework

*Mikhail Rodin* Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization|

h3. March, 2020

|5, #3137|-*Elena Voskoboy* Hybrid VAE for NLG-

*Mikhail Liz* Deep learning for symbolic mathematics

*Vassily Baranov* Distilling knowledge

-*Andrey Yashkin*-

*Sergey Garmaev* Reservoir Computing|

|12, #3138|*Oladotun Aluko* NASNet and AutoML

*Watana Pongsapas*  Deep learning: A Generic approach for extreme condition traffic

*Kirill Kalmutsky* Variational Quantum Circuits and Deep Reinforcement Learning

*Andrey Yashkin* Quantum circuit learning|

|19, #3139|*-Geoffroy de Felcourt-*

*Elena Voskoboy* Hybrid VAE for NLG

~~25 min slot~~|

|26, #3190|*Omid Razizadeh* Reynolds Averaged Turbulence Modeling using Deep Neural Networks with Embedded Invariance.

*Omid Razizadeh* Master thesis

*Kaivalya Pandey* Deep Reinforcement Learning

-*Alix Bernard* Deep Learning based Approach to Reduced Order Modelling-.|

h3. February, 2020

|6, #3133|Planning the semester|

|13, #3133|Planning the semester|

|20, #3136|*Nikita Nikolaev* Zero and Few shot learning

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|27, #3135|*Daria Pirozhkova* ERNIE

-*Sergey Garmaev* Reservoir Computing-

~~25 min slot~~

~~25 min slot~~|

h2. Schedule 2019, fall

Thursday, 18:10, cab 5239 NSU new building

h3. December, 2019

|5, #2819|*Rohan Rahore* “Why Should I Trust You?” Explaining the Predictions of Any Classifier

*Jetina Tsvaki* Thesis

*Omid Razizadeh* Thesis

-*Mihail Rodin* Style transfer-

-*Mohammed Sweilam*-|

|12, #2860|*Ravi Kumar* Thesis

*Raphael Blankson*

*Nikita Nikolaev*

*Abhishek Saxena*

*Rishabh Tiwarri*|

|19, #2946|Conducted by *Kaivalya Anand Pandey*

*Jetina Tsvaki* Paper

-*Elizaveta Tagirova* Paper with code: Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme-

-*Elizaveta Tagirova* Master thesis-

-*Vladislav Panferov*-

*Mikhail Liz* CosFace

*Alexander Rusnak*|

|26, #|*Mihail Rodin* Style transfer

*Mohammed Sweilam*

-*Alexander Rusnak*-

*Owen Siyoto* Master thesis

*Owen Siyoto* Efficient Net

Rescheduled:

* *Elizaveta Tagirova* Paper with code: Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme-

* *Elizaveta Tagirova* Master thesis

* *Vladislav Panferov*|

h3. November, 2019

|7, #2660|*Sergey Garmaev*

*Dinesh Reddy*

*Daria Pirozhkova*

-*Oladotun Aluko*-

*Ravi Kumar* Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge|

|14, #2720|*Roman Kozinets*, Weight Agnostic Neural Networks

*Roman Kozinets*, Master thesis

*Elena Voskoboy* A neural algorithm of artistic style

*Alix Bernard*

-*Oladotun Aluko*-|

|21, #2726|*Kaivalya Pandey*

*Alexander Donets*

-*Rishabh Tiwari*-

*Andrey Yashkin*

*Oladotun Aluko*|

|28, #2766|*Alexey Korolev*

*Kirill Kalmutskiy*

*Mukul Vishwas*

*Antoine Kristanek*|

h3. October, 2019

|3, #2447|~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|10, #2456|Scientific Advisor: prof. Yakovenko S.N.

Scientific Advisor: Postovalov S.N.

Scientific Advisor: Bondarenko I., Batura T.V.

~~25 min slot~~|

|17, #2473|*Munyaradzi Njera* Paper

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|24, #|Scientific Advisor: prof. Palchunov D.E.

*Munyaradzi Njera* Thesis

*Vassily Baranov*|

|31, #2638|*Omid Razizadeh*, Data-driven predictive using field inversion

~~25 min slot~~

*Watana Pongsapas*

-*Ravi Kumar* Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge-|

h3. September, 2019

1. Introduction

2. Scientific advisors presentations: https://trello.com/b/859tElZm/scientfic-advisors-19-21

Presented:

# Taylakov D. (Digital Field Technology)

# Kolonin A.

# Okunev A.

# Usov E. (NNTC.pro)

To be presented:

# ... see https://trello.com/b/859tElZm/scientfic-advisors-19-21

3. Planning the semester #2435 (20.09.2019, 26.09.2019)

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.

*Ravi Kumar* Course work

-*Klim Markelov* Master thesis-

*Roman Kozinets* Master thesis (imaging)

*Anton Dorozhko* Reinforcement Learning for long-term reward optimization in recommender systems (Master thesis)

*Omid Razizadeh* Coursework: Detecting Alzheimer's disease using different machine learning approaches

*Artem Sergeev* Paper: Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

*Artem Sergeev* Master Thesis|

|16, #|*Jetina Tsvaki* Master thesis

*Anik Chakrabarthy* Master thesis

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

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

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

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

h3. April, 2019

|25, #|Open Seminar jointly with Open Data Science Siberia

*Andrey Zubkov* Master thesis: Separability of silent speech phonemes for English language. Speaker and session independence.

*Evgeniy Kurochkin* Master thesis

*Alexandra Luchkina* Master thesis

*Leyuan Sheng* Master thesis: Text to speech synthesis using Generative Adversarial networks for speech enhancement.

*Malysheva Anastasia* Master thesis: The development and research of the prediction methods for time series obtained by the combination of different patterns.

*Olga Yakovenko* Course work

*Juan Pinzon* Master thesis: Sentiment Analysis in Social Media Texts (Spanish language)

Video: https://www.youtube.com/watch?v=T7Oa4hBR3g4|

|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- replaced by

*Natalia Loukashevich* Modern trends on NLP (Tochka Kipenia, Academpark, 16:00, 18.04.2019)|

|11, #2164|*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, #2146|*Roman Kozinets* CNN for speech command recognition. Review

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

*Akilesh Sivaswamy* Master thesis: Data classification using superposition and HMM

*Madina Tussupova* Master Thesis: Determination of grammatical categories using machine learning algorithms

*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, #2105|-*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]]