
Realworld attack on MTCNN face detection system
Recent studies proved that deep learning approaches achieve remarkable r...
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Interpolated Adjoint Method for Neural ODEs
In this paper, we propose a method, which allows us to alleviate or comp...
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Pairwise Augmented GANs with Adversarial Reconstruction Loss
We propose a novel autoencoding model called Pairwise Augmented GANs. We...
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Towards Understanding Normalization in Neural ODEs
Normalization is an important and vastly investigated technique in deep ...
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Variance reduction via empirical variance minimization: convergence and complexity
In this paper we propose and study a generic variance reduction approach...
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Neural networks catching up with finite differences in solving partial differential equations in higher dimensions
Fully connected multilayer perceptrons are used for obtaining numerical ...
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Enhancing approximation abilities of neural networks by training derivatives
Method for increasing precision of feedforward networks is presented. Wi...
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Backpropagation generalized for output derivatives
Backpropagation algorithm is the cornerstone for neural network analysis...
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Simultaneous Matrix Diagonalization for Structural Brain Networks Classification
This paper considers the problem of brain disease classification based o...
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Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems
In this paper, we propose a novel ranking framework for collaborative fi...
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Multiclass classification: mirror descent approach
We consider the problem of multiclass classification and a stochastic o...
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Exponential Machines
Modeling interactions between features improves the performance of machi...
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Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning
Transductive learning considers situations when a learner observes m lab...
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Pairwise Quantization
We consider the task of lossy compression of highdimensional vectors th...
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Differentiable lower bound for expected BLEU score
In natural language processing tasks performance of the models is often ...
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Emotion Recognition From Speech With Recurrent Neural Networks
In this paper the task of emotion recognition from speech is considered....
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When are epsilonnets small?
In many interesting situations the size of epsilonnets depends only on ...
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Testing Docker Performance for HPC Applications
The main goal for this article is to compare performance penalties when ...
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An Accelerated Method for DerivativeFree Smooth Stochastic Convex Optimization
We consider an unconstrained problem of minimization of a smooth convex ...
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Avoiding overfitting of multilayer perceptrons by training derivatives
Resistance to overfitting is observed for neural networks trained with e...
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On LDPC Code Based Massive RandomAccess Scheme for the Gaussian Multiple Access Channel
This paper deals with the problem of massive random access for Gaussian ...
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Gradient Descentbased Doptimal Design for the LeastSquares Polynomial Approximation
In this work, we propose a novel sampling method for Design of Experimen...
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Variational Bidomain Triplet Autoencoder
We investigate deep generative models, which allow us to use training da...
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Semiparametric Image Inpainting
This paper introduces a semiparametric approach to image inpainting for...
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Foreign English Accent Adjustment by Learning Phonetic Patterns
Stateoftheart automatic speech recognition (ASR) systems struggle wit...
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Asymptotically Optimal Pointwise and Minimax Changepoint Detection for General Stochastic Models With a Composite PostChange Hypothesis
A weighted ShiryaevRoberts change detection procedure is shown to appro...
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Robust covariance estimation under L_4L_2 norm equivalence
Let X be a centered random vector taking values in R^d and let Σ= E(X⊗ X...
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Camera Model Identification Using Convolutional Neural Networks
Source camera identification is the process of determining which camera ...
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Uniform HansonWright type concentration inequalities for unbounded entries via the entropy method
This paper is devoted to uniform versions of the HansonWright inequalit...
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On the Complexity of Approximating Wasserstein Barycenter
We study the complexity of approximating Wassertein barycenter of m disc...
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Preconditioning Kaczmarz method by sketching
We propose a new method for preconditioning Kaczmarz method by sketching...
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Importance of Copying Mechanism for News Headline Generation
News headline generation is an essential problem of text summarization b...
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Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language
The paper introduces methods of adaptation of multilingual masked langua...
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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...
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Resolving Gendered Ambiguous Pronouns with BERT
Pronoun resolution is part of coreference resolution, the task of pairin...
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Unsupervised Neural Quantization for CompressedDomain Similarity Search
We tackle the problem of unsupervised visual descriptors compression, wh...
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Relevance Proximity Graphs for Fast Relevance Retrieval
In plenty of machine learning applications, the most relevant items for ...
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OFDMA Resource Allocation for RealTime Applications in IEEE 802.11ax Networks
Support of realtime applications that impose strict requirements on pac...
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Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
Nowadays, deep neural networks (DNNs) have become the main instrument fo...
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Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs
Learning useful representations is a key ingredient to the success of mo...
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Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs
Learning useful representations is a key ingredient to the success of mo...
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Multidomain CT metal artifacts reduction using partial convolution based inpainting
Recent CT Metal Artifacts Reduction (MAR) methods are often based on ima...
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Clustering as a means of leader selection in consensus networks
In the leaderfollower approach, one or more agents are selected as lead...
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Numerical modeling of thin anisotropic composite membrane under dynamic load
This work aims to describe a mathematical model and a numerical method t...
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GoalOriented MultiTask BERTBased Dialogue State Tracker
Dialogue State Tracking (DST) is a core component of virtual assistants ...
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Editable Neural Networks
These days deep neural networks are ubiquitously used in a wide range of...
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Probing Criticality in Quantum Spin Chains with Neural Networks
The numerical emulation of quantum systems often requires an exponential...
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Application of accelerated fixedpoint algorithms to hydrodynamic wellfracture coupling
The coupled simulations of dynamic interactions between the well, hydrau...
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Interferobot: aligning an optical interferometer by a reinforcement learning agent
Limitations in acquiring training data restrict potential applications o...
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Big GANs Are Watching You: Towards Unsupervised Object Segmentation with OfftheShelf Generative Models
Since collecting pixellevel groundtruth data is expensive, unsupervised...
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