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An improved helmet detection method for YOLOv3 on an unbalanced dataset


Authors:  RuiGeng, YixuanMa, WanhongHuang....
Published date-11/09/2020
Tasks:  DataAugmentation

Abstract: The YOLOv3 target detection algorithm is widely used in industry due to its high speed and high accuracy, but it has some limitations, such as the accuracy degradation of unbalanced …

Geometric Deep Reinforcement Learning for Dynamic DAG Scheduling


Authors:  NathanGrinsztajn, OlivierBeaumont, EmmanuelJeannot....
Published date-11/09/2020
Tasks:  CombinatorialOptimization

Abstract: In practice, it is quite common to face combinatorial optimization problems which contain uncertainty along with non-determinism and dynamicity. These three properties call for appropriate algorithms; reinforcement learning (RL) is …

Parameterized Explainer for Graph Neural Network


Authors:  DongshengLuo, WeiCheng, DongkuanXu....
Published date-11/09/2020
Tasks:  GraphClassification

Abstract: Despite recent progress in Graph Neural Networks (GNNs), explaining predictions made by GNNs remains a challenging open problem. The leading method independently addresses the local explanations (i.e., important subgraph structure …

What time is it? Temporal Analysis of Novels


Authors:  AllenKim, CharutaPethe, StevenSkiena....
Published date-11/09/2020

Abstract: Recognizing the flow of time in a story is a crucial aspect of understanding it. Prior work related to time has primarily focused on identifying temporal expressions or relative sequencing …

SplitEasy: A Practical Approach for Training ML models on Mobile Devices in a split second


Authors:  KamaleshPalanisamy, VivekKhimani, MoinHussainMoti....
Published date-11/09/2020

Abstract: Modern mobile devices, although resourceful, cannot train state-of-the-art machine learning models without the assistance of servers, which require access to privacy-sensitive user data. Split learning has recently emerged as a …

Long Range Arena: A Benchmark for Efficient Transformers


Authors:  YiTay, MostafaDehghani, SamiraAbnar....
Published date-11/08/2020

Abstract: Transformers do not scale very well to long sequence lengths largely because of quadratic self-attention complexity. In the recent months, a wide spectrum of efficient, fast Transformers have been proposed …

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