Moscow Institute of Physics and Technology

∙ Dolgoprudny , Russian Federation ∙ 0 followers

Main page of the Moscow Institute of Physics and Technology. MIPT is one of the leading technical universities in Russia. The Institute rightfully occupies a leading place in quality admission of applicants and qualified training of graduates.

Real-world attack on MTCNN face detection system

Recent studies proved that deep learning approaches achieve remarkable r...
10/14/2019 ∙ by Edgar Kaziakhmedov, et al. ∙ 16 ∙ share

read it
Interpolated Adjoint Method for Neural ODEs

In this paper, we propose a method, which allows us to alleviate or comp...
03/11/2020 ∙ by Talgat Daulbaev, et al. ∙ 12 ∙ share

read it
Pairwise Augmented GANs with Adversarial Reconstruction Loss

We propose a novel autoencoding model called Pairwise Augmented GANs. We...
10/11/2018 ∙ by Aibek Alanov, et al. ∙ 8 ∙ share

read it
Towards Understanding Normalization in Neural ODEs

Normalization is an important and vastly investigated technique in deep ...
04/20/2020 ∙ by Julia Gusak, et al. ∙ 2 ∙ share

read it
Variance reduction via empirical variance minimization: convergence and complexity

In this paper we propose and study a generic variance reduction approach...
12/13/2017 ∙ by D. Belomestny, et al. ∙ 0 ∙ share

read it
Neural networks catching up with finite differences in solving partial differential equations in higher dimensions

Fully connected multilayer perceptrons are used for obtaining numerical ...
12/14/2017 ∙ by V. I. Avrutskiy, et al. ∙ 0 ∙ share

read it
Enhancing approximation abilities of neural networks by training derivatives

Method for increasing precision of feedforward networks is presented. Wi...
12/12/2017 ∙ by V. I. Avrutskiy, et al. ∙ 0 ∙ share

read it
Backpropagation generalized for output derivatives

Backpropagation algorithm is the cornerstone for neural network analysis...
12/12/2017 ∙ by V. I. Avrutskiy, et al. ∙ 0 ∙ share

read it
Simultaneous Matrix Diagonalization for Structural Brain Networks Classification

This paper considers the problem of brain disease classification based o...
10/14/2017 ∙ by Nikita Mokrov, et al. ∙ 0 ∙ share

read it
Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems

In this paper, we propose a novel ranking framework for collaborative fi...
04/29/2017 ∙ by Sumit Sidana, et al. ∙ 0 ∙ share

read it
Multi-class classification: mirror descent approach

We consider the problem of multi-class classification and a stochastic o...
06/30/2016 ∙ by Daria Reshetova, et al. ∙ 0 ∙ share

read it
Exponential Machines

Modeling interactions between features improves the performance of machi...
05/12/2016 ∙ by Alexander Novikov, et al. ∙ 0 ∙ share

read it
Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning

Transductive learning considers situations when a learner observes m lab...
05/12/2015 ∙ by Ilya Tolstikhin, et al. ∙ 0 ∙ share

read it
Pairwise Quantization

We consider the task of lossy compression of high-dimensional vectors th...
06/05/2016 ∙ by Artem Babenko, et al. ∙ 0 ∙ share

read it
Differentiable lower bound for expected BLEU score

In natural language processing tasks performance of the models is often ...
12/13/2017 ∙ by Vlad Zhukov, et al. ∙ 0 ∙ share

read it
Emotion Recognition From Speech With Recurrent Neural Networks

In this paper the task of emotion recognition from speech is considered....
01/27/2017 ∙ by Vladimir Chernykh, et al. ∙ 0 ∙ share

read it
When are epsilon-nets small?

In many interesting situations the size of epsilon-nets depends only on ...
11/28/2017 ∙ by Andrey Kupavskii, et al. ∙ 0 ∙ share

read it
Testing Docker Performance for HPC Applications

The main goal for this article is to compare performance penalties when ...
04/19/2017 ∙ by Alexey Ermakov, et al. ∙ 0 ∙ share

read it
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization

We consider an unconstrained problem of minimization of a smooth convex ...
02/25/2018 ∙ by Pavel Dvurechensky, et al. ∙ 0 ∙ share

read it
Avoiding overfitting of multilayer perceptrons by training derivatives

Resistance to overfitting is observed for neural networks trained with e...
02/28/2018 ∙ by V. I. Avrutskiy, et al. ∙ 0 ∙ share

read it
On LDPC Code Based Massive Random-Access Scheme for the Gaussian Multiple Access Channel

This paper deals with the problem of massive random access for Gaussian ...
03/22/2018 ∙ by Luiza Medova, et al. ∙ 0 ∙ share

read it
Gradient Descent-based D-optimal Design for the Least-Squares Polynomial Approximation

In this work, we propose a novel sampling method for Design of Experimen...
06/18/2018 ∙ by V. P. Zankin, et al. ∙ 0 ∙ share

read it
Variational Bi-domain Triplet Autoencoder

We investigate deep generative models, which allow us to use training da...
06/22/2018 ∙ by Rita Kuznetsova, et al. ∙ 0 ∙ share

read it
Semi-parametric Image Inpainting

This paper introduces a semi-parametric approach to image inpainting for...
07/08/2018 ∙ by Karim Iskakov, et al. ∙ 0 ∙ share

read it
Foreign English Accent Adjustment by Learning Phonetic Patterns

State-of-the-art automatic speech recognition (ASR) systems struggle wit...
07/09/2018 ∙ by Fedor Kitashov, et al. ∙ 0 ∙ share

read it
Asymptotically Optimal Pointwise and Minimax Changepoint Detection for General Stochastic Models With a Composite Post-Change Hypothesis

A weighted Shiryaev-Roberts change detection procedure is shown to appro...
07/24/2018 ∙ by Serguei Pergamenchtchikov, et al. ∙ 0 ∙ share

read it
Robust covariance estimation under L_4-L_2 norm equivalence

Let X be a centered random vector taking values in R^d and let Σ= E(X⊗ X...
09/27/2018 ∙ by Shahar Mendelson, et al. ∙ 0 ∙ share

read it
Camera Model Identification Using Convolutional Neural Networks

Source camera identification is the process of determining which camera ...
10/06/2018 ∙ by Artur Kuzin, et al. ∙ 0 ∙ share

read it
Uniform Hanson-Wright type concentration inequalities for unbounded entries via the entropy method

This paper is devoted to uniform versions of the Hanson-Wright inequalit...
12/09/2018 ∙ by Yegor Klochkov, et al. ∙ 0 ∙ share

read it
On the Complexity of Approximating Wasserstein Barycenter

We study the complexity of approximating Wassertein barycenter of m disc...
01/24/2019 ∙ by Alexey Kroshnin, et al. ∙ 0 ∙ share

read it
Preconditioning Kaczmarz method by sketching

We propose a new method for preconditioning Kaczmarz method by sketching...
03/05/2019 ∙ by Alexandr Katrutsa, et al. ∙ 0 ∙ share

read it
Importance of Copying Mechanism for News Headline Generation

News headline generation is an essential problem of text summarization b...
04/25/2019 ∙ by Ilya Gusev, et al. ∙ 0 ∙ share

read it
Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language

The paper introduces methods of adaptation of multilingual masked langua...
05/17/2019 ∙ by Yuri Kuratov, et al. ∙ 0 ∙ share

read it
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent

In this paper we introduce a unified analysis of a large family of varia...
05/27/2019 ∙ by Eduard Gorbunov, et al. ∙ 0 ∙ share

read it
Resolving Gendered Ambiguous Pronouns with BERT

Pronoun resolution is part of coreference resolution, the task of pairin...
06/03/2019 ∙ by Matei Ionita, et al. ∙ 0 ∙ share

read it
Unsupervised Neural Quantization for Compressed-Domain Similarity Search

We tackle the problem of unsupervised visual descriptors compression, wh...
08/11/2019 ∙ by Stanislav Morozov, et al. ∙ 0 ∙ share

read it
Relevance Proximity Graphs for Fast Relevance Retrieval

In plenty of machine learning applications, the most relevant items for ...
08/19/2019 ∙ by Stanislav Morozov, et al. ∙ 0 ∙ share

read it
OFDMA Resource Allocation for Real-Time Applications in IEEE 802.11ax Networks

Support of real-time applications that impose strict requirements on pac...
09/02/2019 ∙ by Evgeny Avdotin, et al. ∙ 0 ∙ share

read it
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Nowadays, deep neural networks (DNNs) have become the main instrument fo...
09/13/2019 ∙ by Sergei Popov, et al. ∙ 0 ∙ share

read it
Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs

Learning useful representations is a key ingredient to the success of mo...
10/08/2019 ∙ by Denis Mazur, et al. ∙ 0 ∙ share

read it
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

Learning useful representations is a key ingredient to the success of mo...
10/08/2019 ∙ by Denis Mazur, et al. ∙ 0 ∙ share

read it
Multi-domain CT metal artifacts reduction using partial convolution based inpainting

Recent CT Metal Artifacts Reduction (MAR) methods are often based on ima...
11/13/2019 ∙ by Artem Pimkin, et al. ∙ 0 ∙ share

read it
Clustering as a means of leader selection in consensus networks

In the leader-follower approach, one or more agents are selected as lead...
12/01/2019 ∙ by Natalia Basimova, et al. ∙ 0 ∙ share

read it
Numerical modeling of thin anisotropic composite membrane under dynamic load

This work aims to describe a mathematical model and a numerical method t...
01/03/2020 ∙ by Vitalii Aksenov, et al. ∙ 0 ∙ share

read it
Goal-Oriented Multi-Task BERT-Based Dialogue State Tracker

Dialogue State Tracking (DST) is a core component of virtual assistants ...
02/05/2020 ∙ by Pavel Gulyaev, et al. ∙ 0 ∙ share

read it
Editable Neural Networks

These days deep neural networks are ubiquitously used in a wide range of...
04/01/2020 ∙ by Anton Sinitsin, et al. ∙ 0 ∙ share

read it
Probing Criticality in Quantum Spin Chains with Neural Networks

The numerical emulation of quantum systems often requires an exponential...
05/05/2020 ∙ by A Berezutskii, et al. ∙ 0 ∙ share

read it
Application of accelerated fixed-point algorithms to hydrodynamic well-fracture coupling

The coupled simulations of dynamic interactions between the well, hydrau...
05/01/2020 ∙ by Vitalii Aksenov, et al. ∙ 0 ∙ share

read it
Interferobot: aligning an optical interferometer by a reinforcement learning agent

Limitations in acquiring training data restrict potential applications o...
06/03/2020 ∙ by Dmitry Sorokin, et al. ∙ 0 ∙ share

read it
Big GANs Are Watching You: Towards Unsupervised Object Segmentation with Off-the-Shelf Generative Models

Since collecting pixel-level groundtruth data is expensive, unsupervised...
06/08/2020 ∙ by Andrey Voynov, et al. ∙ 0 ∙ share

read it

Moscow Institute of Physics and Technology

Featured Researchers