Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker. (⭐ 10884)
Olive production is an important tree crop in Mediterranean climates. However, olive yield varies significantly due to climate change. Accurately estimating yield using remote sensing and machine learning remains a complex challenge. In this study, w...
Random linear mappings are widely used in modern signal processing, compressed sensing and machine learning. These mappings may be used to embed the data into a significantly lower dimension while at the same time preserving useful information. This...
Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the most diff...
DiffSharp is an algorithmic differentiation or automatic differentiation (AD) library for the .NET ecosystem, which is targeted by the C# and F# languages, among others. The library has been designed with machine learning applications in mind, allowi...
Community detection in graphs, data clustering, and local pattern mining are three mature fields of data mining and machine learning. In recent years, attributed subgraph mining is emerging as a new powerful data mining task in the intersection of th...
2009. Home Max Minghella Set for The Darkest Hour Archived 10 November 2013 at the Wayback Machine "Mindy Project Scoop: Social Network Actor Max Minghella
Max Welling (born 1968) is a Dutch computer scientist in machine learning at the University of Amsterdam. In August 2017, the university spin-off Scyfer
Purpose: Terminology is the set of technical words or expressions used in specific contexts, which denotes the core concept in a formal discipline and is usually applied in the fields of machine translation, information retrieval, information extract...
Consolidated access to current and reliable terms from different subject fields and languages is necessary for content creators and translators. Terminology is also needed in AI applications such as machine translation, speech recognition, informatio...
Terminology correctness is important in the downstream application of machine translation, and a prevalent way to ensure this is to inject terminology constraints into a translation system. In our submission to the WMT 2023 terminology translation ta...
Bản dịch của cuốn "Interpretable Machine Learning: A Guide for Making Black Box Models Explainable" sang tiếng Việt (⭐ 118)
The intriguing phenomenon of adversarial examples has attracted significant attention in machine learning and what might be more surprising to the community is the existence of universal adversarial perturbations (UAPs), i.e. a single perturbation to...
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Teaching materials for the machine learning and deep learning classes at Stanford and Cornell (⭐ 1135)
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Points: 2928 | Comments: 1514 | Author: davikr
Machine learning and artificial intelligence conferences such as NeurIPS and ICML now regularly receive tens of thousands of submissions, posing significant challenges to maintaining the quality and consistency of the peer review process. This challe...
State Space Model (SSM) is a mathematical model used to describe and analyze the behavior of dynamic systems. This model has witnessed numerous applications in several fields, including control theory, signal processing, economics and machine learnin...
Jan 9, 2011 · Well, "homemade" means "made at home" while "handmade" means made by hand, not by a machine. Many "homemade" items are also "handmade," because people who make things at …