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20162026
most citedAlbumentations: fast and flexible image augmentations

2.3k citations

Showing 2018Show all

12 papers · 1 filter

math.PR2018★ 5 cited

On the Itô-Alekseev-Gröbner formula for stochastic differential equations

Anselm Hudde, Martin Hutzenthaler, Arnulf Jentzen +1

In this article we establish a new formula for the difference of a test function of the solution of a stochastic differential equation and of the test function of an Itô process. T…

math.OC2018★ 1 cited

A Linearly Convergent Doubly Stochastic Gauss-Seidel Algorithm for Solving Linear Equations and A Certain Class of Over-Parameterized Optimization Problems

Meisam Razaviyayn, Mingyi Hong, Navid Reyhanian +1

Consider the classical problem of solving a general linear system of equations . It is well known that the (successively over relaxed) Gauss-Seidel scheme and many of its var…

cs.CV2018★ 2.3k cited

Albumentations: fast and flexible image augmentations

Alexander Buslaev, Alex Parinov, Eugene Khvedchenya +2

Data augmentation is a commonly used technique for increasing both the size and the diversity of labeled training sets by leveraging input transformations that preserve output labe…

math.OC2018★ 10 cited

Multi-UAV Interference Coordination via Joint Trajectory and Power Control

Chao Shen, Tsung-Hui Chang, Jie Gong +2

In this paper, we consider an unmanned aerial vehicle-enabled interference channel (UAV-IC), where each of the UAVs communicates with its associated ground terminals (GTs) at t…

math.NA2018★ 48 cited

A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients

Arnulf Jentzen, Diyora Salimova, Timo Welti

In recent years deep artificial neural networks (DNNs) have been successfully employed in numerical simulations for a multitude of computational problems including, for example, ob…

math.NA2018★ 153 cited

A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations

Philipp Grohs, Fabian Hornung, Arnulf Jentzen +1

Artificial neural networks (ANNs) have very successfully been used in numerical simulations for a series of computational problems ranging from image classification/image recogniti…

math.PR2018★ 4 cited

A General Framework of Multi-Armed Bandit Processes by Arm Switch Restrictions

Wenqing Bao, Xiaoqiang Cai, Xianyi Wu

This paper proposes a general framework of multi-armed bandit (MAB) processes by introducing a type of restrictions on the switches among arms evolving in continuous time. The Gitt…

cs.CV2018★ 10 cited

Video Inpainting by Jointly Learning Temporal Structure and Spatial Details

Chuan Wang, Haibin Huang, Xiaoguang Han +1

We present a new data-driven video inpainting method for recovering missing regions of video frames. A novel deep learning architecture is proposed which contains two sub-networks:…

eess.SP2018★ 6 cited

Reinforcement Learning based Multi-Access Control and Battery Prediction with Energy Harvesting in IoT Systems

Man Chu, Hang Li, Xuewen Liao +1

Energy harvesting (EH) is a promising technique to fulfill the long-term and self-sustainable operations for Internet of things (IoT) systems. In this paper, we study the joint acc…

cs.IT2018★ 5 cited

Joint Computation and Communication Cooperation for Energy-Efficient Mobile Edge Computing

Xiaowen Cao, Feng Wang, Jie Xu +2

This paper proposes a novel user cooperation approach in both computation and communication for mobile edge computing (MEC) systems to improve the energy efficiency for latency-con…

q-bio.GN2018★ 2 cited

Joint Analysis of Individual-level and Summary-level GWAS Data by Leveraging Pleiotropy

Mingwei Dai, Xiang Wan, Hao Peng +5

A large number of recent genome-wide association studies (GWASs) for complex phenotypes confirm the early conjecture for polygenicity, suggesting the presence of large number of va…

cs.IT2018★ 4 cited

Max-Min Fairness User Scheduling and Power Allocation in Full-Duplex OFDMA Systems

Xiaozhou Zhang, Tsung-Hui Chang, Ya-Feng Liu +2

In a full-duplex (FD) multi-user network, the system performance is not only limited by the self-interference but also by the co-channel interference due to the simultaneous uplink…