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09/03/2023
On the structure of the Schur complement matrix for the Stokes equation
In this paper, we investigate the structure of the Schur complement matr...
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08/31/2023
Unsupervised evaluation of GAN sample quality: Introducing the TTJac Score
Evaluation metrics are essential for assessing the performance of genera...
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08/31/2023
Robust GAN inversion
Recent advancements in real image editing have been attributed to the ex...
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08/08/2023
Quantization Aware Factorization for Deep Neural Network Compression
Tensor decomposition of convolutional and fully-connected layers is an e...
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07/11/2023
On the efficient preconditioning of the Stokes equations in tight geometries
If the Stokes equations are properly discretized, it is well-known that ...
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06/05/2023
Efficient GPT Model Pre-training using Tensor Train Matrix Representation
Large-scale transformer models have shown remarkable performance in lang...
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05/31/2023
Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
Self-supervised methods received tremendous attention thanks to their se...
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05/08/2023
Adaptive Cross Tubal Tensor Approximation
In this paper, we propose a new adaptive cross algorithm for computing a...
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04/11/2023
TT-SDF2PC: Registration of Point Cloud and Compressed SDF Directly in the Memory-Efficient Tensor Train Domain
This paper addresses the following research question: “can one compress ...
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03/20/2023
Translate your gibberish: black-box adversarial attack on machine translation systems
Neural networks are deployed widely in natural language processing tasks...
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03/14/2023
Multiparticle Kalman filter for object localization in symmetric environments
This study considers the object localization problem and proposes a nove...
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02/05/2023
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction
In this study, we propose a novel SeqMF model to solve the problem of pr...
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01/30/2023
General Covariance Data Augmentation for Neural PDE Solvers
The growing body of research shows how to replace classical partial diff...
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01/28/2023
PROTES: Probabilistic Optimization with Tensor Sampling
We develop new method PROTES for optimization of the multidimensional ar...
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01/12/2023
Machine learning methods for prediction of breakthrough curves in reactive porous media
Reactive flows in porous media play an important role in our life and ar...
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01/08/2023
Mitigating Human and Computer Opinion Fraud via Contrastive Learning
We introduce the novel approach towards fake text reviews detection in c...
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12/25/2022
FMM-Net: neural network architecture based on the Fast Multipole Method
In this paper, we propose a new neural network architecture based on the...
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12/12/2022
Tensor-based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations
Self-attentive transformer models have recently been shown to solve the ...
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09/29/2022
NAG-GS: Semi-Implicit, Accelerated and Robust Stochastic Optimizers
Classical machine learning models such as deep neural networks are usual...
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09/29/2022
Optimization of Functions Given in the Tensor Train Format
Tensor train (TT) format is a common approach for computationally effici...
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09/29/2022
A case study of spatiotemporal forecasting techniques for weather forecasting
The majority of real-world processes are spatiotemporal, and the data ge...
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08/05/2022
Black box approximation in the tensor train format initialized by ANOVA decomposition
Surrogate models can reduce computational costs for multivariable functi...
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08/02/2022
T4DT: Tensorizing Time for Learning Temporal 3D Visual Data
Unlike 2D raster images, there is no single dominant representation for ...
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07/31/2022
Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI
The size and complexity of deep neural networks continue to grow exponen...
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07/13/2022
Cross Tensor Approximation for Image and Video Completion
This paper proposes a general framework to use the cross tensor approxim...
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07/06/2022
Tensor networks in machine learning
A tensor network is a type of decomposition used to express and approxim...
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06/08/2022
Constructive TT-representation of the tensors given as index interaction functions with applications
This paper presents a method to build explicit tensor-train (TT) represe...
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05/12/2022
Direct optimization of BPX preconditioners
We consider an automatic construction of locally optimal preconditioners...
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05/10/2022
Tensor-based Collaborative Filtering With Smooth Ratings Scale
Conventional collaborative filtering techniques don't take into consider...
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05/09/2022
Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks
Collaborative filtering models generally perform better than content-bas...
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04/30/2022
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning
We present a novel procedure for optimization based on the combination o...
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04/25/2022
On the Performance of Machine Learning Methods for Breakthrough Curve Prediction
Reactive flows are important part of numerous technical and environmenta...
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03/21/2022
Hyperbolic Vision Transformers: Combining Improvements in Metric Learning
Metric learning aims to learn a highly discriminative model encouraging ...
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02/23/2022
Extension of Dynamic Mode Decomposition for dynamic systems with incomplete information based on t-model of optimal prediction
The Dynamic Mode Decomposition has proved to be a very efficient techniq...
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02/21/2022
Survey on Large Scale Neural Network Training
Modern Deep Neural Networks (DNNs) require significant memory to store w...
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02/14/2022
Understanding DDPM Latent Codes Through Optimal Transport
Diffusion models have recently outperformed alternative approaches to mo...
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02/02/2022
Smoothed Embeddings for Certified Few-Shot Learning
Randomized smoothing is considered to be the state-of-the-art provable d...
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02/01/2022
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
Memory footprint is one of the main limiting factors for large neural ne...
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01/31/2022
Memory-Efficient Backpropagation through Large Linear Layers
In modern neural networks like Transformers, linear layers require signi...
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11/29/2021
Latent Transformations via NeuralODEs for GAN-based Image Editing
Recent advances in high-fidelity semantic image editing heavily rely on ...
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09/22/2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks
In safety-critical machine learning applications, it is crucial to defen...
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06/13/2021
Generation of the NIR spectral Band for Satellite Images with Convolutional Neural Networks
The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the mult...
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05/12/2021
Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation
Today deep convolutional neural networks (CNNs) push the limits for most...
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04/11/2021
Dynamic Modeling of User Preferences for Stable Recommendations
In domains where users tend to develop long-term preferences that do not...
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03/27/2021
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds
In scientific computing and machine learning applications, matrices and ...
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03/18/2021
Optimal soil sampling design based on the maxvol algorithm
Spatial soil sampling is an integral part of a soil survey aimed at crea...
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03/15/2021
Meta-Solver for Neural Ordinary Differential Equations
A conventional approach to train neural ordinary differential equations ...
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02/16/2021
Solution of the Fokker-Planck equation by cross approximation method in the tensor train format
We propose the novel numerical scheme for solution of the multidimension...
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02/11/2021
Disentangled Representations from Non-Disentangled Models
Constructing disentangled representations is known to be a difficult tas...
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02/08/2021