Federated learning is a machine learning approach where multiple devices collaboratively learn with the help of a parameter server by sharing only their local updates. While gradient-based optimization techniques are widely adopted in this domain, th...
We outline the design and construction of novel robotic arms using machine perception, convolutional neural networks, and symbolic AI for logical control and affordance indexing. We describe our robotic arms built with a humanlike mechanical configur...
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Ruby finite-state-machine-inspired API for modeling workflow (⭐ 1796)
MEEG-44403/54403 Machine Learning for Mechanical Engineers at the University of Arkansas (⭐ 45)
What happens when generative machine learning models are pretrained on web-scale datasets containing data generated by earlier models? Some prior work warns of "model collapse" as the web is overwhelmed by synthetic data; other work suggests the prob...
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Adjective unanswered (not comparable) That has not been answered or addressed. The flashing light on the answering machine bore testimony to the unanswered call.
WIDIA is a brand for machinists, mechanical engineers, and machine shop owners who are depending on a reliable tool to keep their shop running through the night. The brand offers a full portfolio of …
An aspiring data scientist with expertise in machine learning, data analysis, and predictive modeling, developed through the MIT Applied Data Science Program. My projects include predictive modeling, feature engineering, model evaluation, and exploratory data…
This repository contains human electrocardiogram data (ECG) data used in Wavelet Toolbox machine and deep learning examples (⭐ 60)
A list of papers for physiological signal classification using machine learning/deep learning. (⭐ 246)
Human emotions entail a complex set of behavioral, physiological and cognitive changes. Current state-of-the-art models fuse the behavioral and physiological components using classic machine learning, rather than recent deep learning techniques. We p...
Samidoun condemned the joint US-Israeli attack on Iran, while SJP called on chapters to mobilize to "defend Iran’s sovereignty, and break the zionist war machine."
It is an old idea to use gradient flows or time-discretized variants thereof as methods for solving minimization problems. In some applications, for example in machine learning contexts, it is important to know that for generic initial data, gradient...
Deep neural networks on over 50 classification problems from the UC Irvine Machine Learning Repository (⭐ 27)
The classical problem in computer vision, image processing, and machine vision is that of determining whether or not the image data contains some specific object, feature, or activity. Different varieties of the recognition problem are described in the literat…
Approximate nearest neighbor (ANN) search is a performance-critical component of many machine learning pipelines. Rigorous benchmarking is essential for evaluating the performance of vector indexes for ANN search. However, the datasets of the existin...
Federated Learning (FL) allows edge devices to collaboratively learn a shared prediction model while keeping their training data on the device, thereby decoupling the ability to do machine learning from the need to store data in the cloud. Despite th...
Automatic speech recognition and spoken dialogue systems have made great advances through the use of deep machine learning methods. This is partly due to greater computing power but also through the large amount of data available in common languages,...