Project guidlines could be found here
Some previous project examples could be found here. 2018 year projects are available here.
Team | Project |
---|---|
Mikhail Moldovan, Aleksandra Ozerova | Decomposition of expression matrices obtained from single cell RNA-seq |
Nikita Borovkov, Filipp Furaev | Scaling SVD recommender systems |
Jamil Zakirov, Emil Zakirov, Anna Rudenko, Galina Burdukovskaya, Evgeny Zholkovskiy | Use different tensor decomposition techniques for CNN compression |
Hekmat Taherinejad, Hamidreza Behjoo, Rahim Tariverdi, Kodirjon Akhmedov | Probabilistic Matrix Analysis |
Nikita Mokrov, Natalya Basimova, Ilya Selnitskiy, Ilya Zakharkin | On the new method of Hessian estimation for effective neural network optimization |
Sofya Dymchenko, Ruslan Khaidurov, Dmitry Vypiraylenko | Banach Wasserstein GAN -- Skoltech edition |
Mikhail Salnikov, Ildar Abdrakhmanov, Anastasia Remizova | Singular Value Decomposition for prevention of Graph Convolutional Networks overfitting |
Alexandra Varets, Valeriya Mikova | Transversality enforced Newton-Raphson algorithm for fast calculation of maximum loadability |
Timur Akhtyamov, Anna Nikolaeva, Samir Mohamed | Online disturbed implementation for Principal Components Analysis (PCA) |
Evgeny Frolov, Daria Frolova, Maksim Valialshchikov | Comparing performance of algorithms of computing Skeleton decomposition |
Inga Bashkirova, Aleksandra Senkevich | Modelling the Semantic Change using Diachronic Word Embedding |
Ruslan Aliev, Max Kan, Georgii Fisher, Vyacheslav Rezyapkin | Efficient dataset subsampling using Hessian of loss fucntion |
Ilya Borovik, Khattiya Pongsirijinda, Jerry Atorigo | Audio watermarking using SVD and Schur Decomposition |
Polina Druzhinina, Kirill Demochkin, Maxim Lunitsin, Maria Bakhanova | Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change |
Dmitry Smorchkov, Ivan Vovk, Grigorii Sotnikov, Vladimir Gogoryan | Compression of Text-to-Speech System |
Daniil Selikhanovych, Elizaveta Noskova, Elizaveta Kiseleva | Shampoo: Preconditioned Stochastic Tensor Optimization |
Danil Kirichik, Pavel Shevchuk | Finding markov stationary distribution using eigenvectors approach |
Aynur Maksutov, Danil Karpushkin, Karim Gizatullin, Oluwafemi Olaleke | Independent component analysis for the Cocktail Party Problem |
Maria Begicheva, Arman Tsaturyan | Recommendation of articles |
Ivan Zakazov, Artem Zabolotnyi, Yerzhan Imanmalik | SVD for EEG analysis |
Kirill Shcherbakov, Egor Sevriugov | Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization |
Arman Tsaturyan, Maria Begicheva, Olga Novitskaia | Recommendation of scientific articles |
Angelina Yaroshenko, Elvira Zainulina, Lyubov Kupriyanova, Dmitrii Puzyrev | Optimal tensor decomposition for word embeddings composition |
Vitaly Protasov, Kristina Ivanova, Veronika Kuznetsova | Enhanced image approximation using shifted rank-1 reconstruction |
Daria Gazizova, Alexander Shumilov, Vladimir Dmitriev, Veronika Zorina | SVD for compression of results from FEM |
Daria Musatkina, Igor Markov, Aleksei Kalinov, Denis Belyakov | Efficient ways of computing Schatten p-norm and it's applications |
Nikita Bekezin, Alexander Selivanov | Dimensionality Reduction of Massive Sparse Datasets Using Coresets |
Viktor Shipitsin, Aleksei Viatkin, Anton Voronov, Alexander Rubinstein | Word embedding interpretation |
Vadim Selyutin, Egor Gladin, Semyon Glushkov, Natalia Uspenskaia | Fast MLE for ML |
Vladislav Alekseev, Danil Bragin, Victoria Dochkina | Dimension reductive techniques in porosity measurement of carbonate thin section images |
Lyubov Kupriyanova, Dmitrii Puzyrev, Angelina Yaroshenko, Elvira Zainulina | Using Dynamic mode decomposition and its modifications for picture edge detection |
Tamerlan Tabolov, Anton Semenkin, Alexander Fritzler, Natasha Soboleva | Domain-adaptive deep network compression |
Mikhail Vasilkovsky, Egor Konyagin, Ekaterina Vorobyeva, Leonid Litovchenko | Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization |
Alexander Borzilov, Aleksandr Artemenkov, Anastasiia Kornilova | Optimizations for DfSM (depth from small motion) algorithms |
Ivan Baybuza, Alexandr Belov, Mariia Kopylova, Miron Kuznetsov | Highlighting key features using factorization |
Vladislav Zhuzhel, Evgenii Guzovskii, Tamara Tsakhilova | Tag clustering and text lableing |
Nikita Petrashen, Nikita Drobyshev, Daniil Svirsky, Dinar Sharafutdinov | Spectral Relaxation for K-means Clustering |
Konstantin Pakulev, Yerzhaisang Taskali, Igor Karpikov | Fundamental matrix estimation via iterative reweighted least-squares |
Mikhail Goncharov | Simple Graph Convolution for Text Classification |