Algorithms

Learning to Rank with XGBoost and GPU

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. XGBoost is a widely used machine learning library, which uses gradient boosting techniques to incrementally build a better model during the training phase by combining multiple weak models. Weak models are generated by computing the gradient descent using […]

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Streamline Your Intel Distribution of OpenVINO Toolkit Development with Deep Learning Workbench

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. Back in 2018, Intel launched the Intel® Distribution of OpenVINO™ toolkit. Since then, it’s been widely adopted by partners and developers to deploy AI-powered applications in various industries, from self-checkout kiosks to medical imaging to industrial robotics.

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Codeplay’s Contribution to DPC++ Brings SYCL Support for NVIDIA GPUs

This blog post was originally published at Codeplay Software’s website. It is reprinted here with the permission of Codeplay Software. Codeplay has been a part of the SYCL™ community from the beginning, and our team has worked with peers from some of the largest semiconductor vendors including Intel and Xilinx for the past 5 years

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“PyTorch Deep Learning Framework: Status and Directions,” a Presentation from Facebook

Joseph Spisak, Product Manager at Facebook, delivers the presentation “PyTorch Deep Learning Framework: Status and Directions” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Spisak gives an update on the Torch deep learning framework and where it’s heading.

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“Current and Planned Standards for Computer Vision and Machine Learning,” a Presentation from the Khronos Group

Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, delivers the presentation “Current and Planned Standards for Computer Vision and Machine Learning” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the

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A Guide to Video Analytics: Applications and Opportunities

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. Introduction In the past few years, video analytics, also known as video content analysis or intelligent video analytics, has attracted increasing interest from both industry and the academic world. Thanks to the enormous advances made in deep learning,

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“Edge/Cloud Tradeoffs and Scaling a Consumer Computer Vision Product,” a Presentation from Cocoon Health

Pavan Kumar, Co-founder and CTO of Cocoon Health (formerly Cocoon Cam), delivers the presentation “Edge/Cloud Tradeoffs and Scaling a Consumer Computer Vision Product” at the Embedded Vision Alliance’s September 2019 Vision Industry and Technology Forum. Kumar explains how his company is evolving its use of edge and cloud vision computing in continuing to bring new

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“Quantizing Deep Networks for Efficient Inference at the Edge,” a Presentation from Facebook

Raghuraman Krishnamoorthi, Software Engineer at Facebook, delivers the presentation “Quantizing Deep Networks for Efficient Inference at the Edge” at the Embedded Vision Alliance’s September 2019 Vision Industry and Technology Forum. Krishnamoorthi gives an overview of practical deep neural network quantization techniques and tools.

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