Moscow Institute of Physics and Technology

research

∙ 07/06/2021

Stateless actor-critic for instance segmentation with high-level priors

Instance segmentation is an important computer vision problem which rema...

Paul Hilt, et al. ∙

research

∙ 10/14/2019

Real-world attack on MTCNN face detection system

Recent studies proved that deep learning approaches achieve remarkable r...

Edgar Kaziakhmedov, et al. ∙

research

∙ 03/11/2020

Interpolated Adjoint Method for Neural ODEs

In this paper, we propose a method, which allows us to alleviate or comp...

Talgat Daulbaev, et al. ∙

research

∙ 02/11/2022

Similarity learning for wells based on logging data

One of the first steps during the investigation of geological objects is...

Evgenia Romanenkova, et al. ∙

research

∙ 10/11/2018

Pairwise Augmented GANs with Adversarial Reconstruction Loss

We propose a novel autoencoding model called Pairwise Augmented GANs. We...

Aibek Alanov, et al. ∙

research

∙ 09/17/2021

Landmark Policy Optimization for Object Navigation Task

This work studies object goal navigation task, which involves navigating...

Aleksey Staroverov, et al. ∙

research

∙ 02/17/2022

When, Why, and Which Pretrained GANs Are Useful?

The literature has proposed several methods to finetune pretrained GANs ...

Timofey Grigoryev, et al. ∙

research

∙ 04/20/2020

Towards Understanding Normalization in Neural ODEs

Normalization is an important and vastly investigated technique in deep ...

Julia Gusak, et al. ∙

research

∙ 12/13/2017

Variance reduction via empirical variance minimization: convergence and complexity

In this paper we propose and study a generic variance reduction approach...

D. Belomestny, et al. ∙

research

∙ 12/14/2017

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

Fully connected multilayer perceptrons are used for obtaining numerical ...

V. I. Avrutskiy, et al. ∙

research

∙ 12/12/2017

Enhancing approximation abilities of neural networks by training derivatives

Method for increasing precision of feedforward networks is presented. Wi...

V. I. Avrutskiy, et al. ∙

research

∙ 12/12/2017

Backpropagation generalized for output derivatives

Backpropagation algorithm is the cornerstone for neural network analysis...

V. I. Avrutskiy, et al. ∙

research

∙ 10/14/2017

Simultaneous Matrix Diagonalization for Structural Brain Networks Classification

This paper considers the problem of brain disease classification based o...

Nikita Mokrov, et al. ∙

research

∙ 04/29/2017

Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems

In this paper, we propose a novel ranking framework for collaborative fi...

Sumit Sidana, et al. ∙

research

∙ 06/30/2016

Multi-class classification: mirror descent approach

We consider the problem of multi-class classification and a stochastic o...

Daria Reshetova, et al. ∙

research

∙ 05/12/2016

Exponential Machines

Modeling interactions between features improves the performance of machi...

Alexander Novikov, et al. ∙

research

∙ 05/12/2015

Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning

Transductive learning considers situations when a learner observes m lab...

Ilya Tolstikhin, et al. ∙

research

∙ 06/05/2016

Pairwise Quantization

We consider the task of lossy compression of high-dimensional vectors th...

Artem Babenko, et al. ∙

research

∙ 12/13/2017

Differentiable lower bound for expected BLEU score

In natural language processing tasks performance of the models is often ...

Vlad Zhukov, et al. ∙

research

∙ 01/27/2017

Emotion Recognition From Speech With Recurrent Neural Networks

In this paper the task of emotion recognition from speech is considered....

Vladimir Chernykh, et al. ∙

research

∙ 11/28/2017

When are epsilon-nets small?

In many interesting situations the size of epsilon-nets depends only on ...

Andrey Kupavskii, et al. ∙

research

∙ 04/19/2017

Testing Docker Performance for HPC Applications

The main goal for this article is to compare performance penalties when ...

Alexey Ermakov, et al. ∙

research

∙ 02/25/2018

An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization

We consider an unconstrained problem of minimization of a smooth convex ...

Pavel Dvurechensky, et al. ∙

research

∙ 02/28/2018

Avoiding overfitting of multilayer perceptrons by training derivatives

Resistance to overfitting is observed for neural networks trained with e...

V. I. Avrutskiy, et al. ∙

research

∙ 03/22/2018

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 ...

Luiza Medova, et al. ∙

research

∙ 06/18/2018

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...

V. P. Zankin, et al. ∙

research

∙ 06/22/2018

Variational Bi-domain Triplet Autoencoder

We investigate deep generative models, which allow us to use training da...

Rita Kuznetsova, et al. ∙

research

∙ 07/08/2018

Semi-parametric Image Inpainting

This paper introduces a semi-parametric approach to image inpainting for...

Karim Iskakov, et al. ∙

research

∙ 07/09/2018

Foreign English Accent Adjustment by Learning Phonetic Patterns

State-of-the-art automatic speech recognition (ASR) systems struggle wit...

Fedor Kitashov, et al. ∙

research

∙ 07/24/2018

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...

Serguei Pergamenchtchikov, et al. ∙

research

∙ 09/27/2018

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...

Shahar Mendelson, et al. ∙

research

∙ 10/06/2018

Camera Model Identification Using Convolutional Neural Networks

Source camera identification is the process of determining which camera ...

Artur Kuzin, et al. ∙

research

∙ 12/09/2018

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...

Yegor Klochkov, et al. ∙

research

∙ 01/24/2019

On the Complexity of Approximating Wasserstein Barycenter

We study the complexity of approximating Wassertein barycenter of m disc...

Alexey Kroshnin, et al. ∙

research

∙ 03/05/2019

Preconditioning Kaczmarz method by sketching

We propose a new method for preconditioning Kaczmarz method by sketching...

Alexandr Katrutsa, et al. ∙

research

∙ 04/25/2019

Importance of Copying Mechanism for News Headline Generation

News headline generation is an essential problem of text summarization b...

Ilya Gusev, et al. ∙

research

∙ 05/17/2019

Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language

The paper introduces methods of adaptation of multilingual masked langua...

Yuri Kuratov, et al. ∙

research

∙ 05/27/2019

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...

Eduard Gorbunov, et al. ∙

research

∙ 06/03/2019

Resolving Gendered Ambiguous Pronouns with BERT

Pronoun resolution is part of coreference resolution, the task of pairin...

Matei Ionita, et al. ∙

research

∙ 08/11/2019

Unsupervised Neural Quantization for Compressed-Domain Similarity Search

We tackle the problem of unsupervised visual descriptors compression, wh...

Stanislav Morozov, et al. ∙

research

∙ 08/19/2019

Relevance Proximity Graphs for Fast Relevance Retrieval

In plenty of machine learning applications, the most relevant items for ...

Stanislav Morozov, et al. ∙

research

∙ 09/02/2019

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

Support of real-time applications that impose strict requirements on pac...

Evgeny Avdotin, et al. ∙

research

∙ 09/13/2019

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Nowadays, deep neural networks (DNNs) have become the main instrument fo...

Sergei Popov, et al. ∙

research

∙ 10/08/2019

Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs

Learning useful representations is a key ingredient to the success of mo...

Denis Mazur, et al. ∙

research

∙ 10/08/2019

Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

Learning useful representations is a key ingredient to the success of mo...

Denis Mazur, et al. ∙

research

∙ 11/13/2019

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

Recent CT Metal Artifacts Reduction (MAR) methods are often based on ima...

Artem Pimkin, et al. ∙

research

∙ 12/01/2019

Clustering as a means of leader selection in consensus networks

In the leader-follower approach, one or more agents are selected as lead...

Natalia Basimova, et al. ∙

research

∙ 01/03/2020

Numerical modeling of thin anisotropic composite membrane under dynamic load

This work aims to describe a mathematical model and a numerical method t...

Vitalii Aksenov, et al. ∙

research

∙ 02/05/2020

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

Dialogue State Tracking (DST) is a core component of virtual assistants ...

Pavel Gulyaev, et al. ∙

research

∙ 04/01/2020

Editable Neural Networks

These days deep neural networks are ubiquitously used in a wide range of...

Anton Sinitsin, et al. ∙

Moscow Institute of Physics and Technology

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