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Software engineering for artificial intelligence and machine learning software: A systematic literature review

Artificial Intelligence (AI) or Machine Learning (ML) systems have been ...
11/07/2020 ∙ by Elizamary Nascimento, et al. ∙ 233 ∙ share

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Combining GANs and AutoEncoders for Efficient Anomaly Detection

In this work, we propose CBiGAN – a novel method for anomaly detection i...
11/16/2020 ∙ by Fabio Carrara, et al. ∙ 117 ∙ share

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Graph Kernels: State-of-the-Art and Future Challenges

Graph-structured data are an integral part of many application domains, ...
11/07/2020 ∙ by Karsten Borgwardt, et al. ∙ 94 ∙ share

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Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking

Deep reinforcement learning has been one of the fastest growing fields o...
11/15/2020 ∙ by Fabio Pardo, et al. ∙ 78 ∙ share

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Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP

Large volumes of interaction logs can be collected from NLP systems that...
11/04/2020 ∙ by Julia Kreutzer, et al. ∙ 73 ∙ share

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Digital Twins: State of the Art Theory and Practice, Challenges, and Open Research Questions

Digital Twin was introduced over a decade ago, as an innovative all-enco...
11/02/2020 ∙ by Angira Sharma, et al. ∙ 73 ∙ share

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When Machine Learning Meets Privacy: A Survey and Outlook

The newly emerged machine learning (e.g. deep learning) methods have bec...
11/24/2020 ∙ by Bo Liu, et al. ∙ 69 ∙ share

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RealAnt: An Open-Source Low-Cost Quadruped for Research in Real-World Reinforcement Learning

Current robot platforms available for research are either very expensive...
11/05/2020 ∙ by Rinu Boney, et al. ∙ 67 ∙ share

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EasyTransfer – A Simple and Scalable Deep Transfer Learning Platform for NLP Applications

The literature has witnessed the success of applying deep Transfer Learn...
11/18/2020 ∙ by Minghui Qiu, et al. ∙ 63 ∙ share

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Local SGD: Unified Theory and New Efficient Methods

We present a unified framework for analyzing local SGD methods in the co...
11/03/2020 ∙ by Eduard Gorbunov, et al. ∙ 62 ∙ share

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Batch Normalization Embeddings for Deep Domain Generalization

Domain generalization aims at training machine learning models to perfor...
11/25/2020 ∙ by Mattia Segù, et al. ∙ 61 ∙ share

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