Results 31 to 40 of about 60,295 (249)
Bolt: Accelerated Data Mining with Fast Vector Compression
, 2017 Vectors of data are at the heart of machine learning and data mining. Recently, vector quantization methods have shown great promise in reducing both the time and space costs of operating on vectors.
Blalock, Davis W, Guttag, John V
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Aspects in Classification Learning - Review of Recent Developments in Learning Vector Quantization
Foundations of Computing and Decision Sciences, 2014 .Classification is one of the most frequent tasks in machine learning. However, the variety of classification tasks as well as classifier methods is huge.
Kaden M. +5 more
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The Classification of Children Gadget Addiction: The Employment of Learning Vector Quantization 3
IT Journal Research and Development, 2020 The addiction of children to gadgets has a massive influence on their social growth. Thus, it is essential to note earlier on the addiction of children to such technologies.
Okfalisa Okfalisa +4 more
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Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Advanced Functional Materials, EarlyView.Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source
Explainable human‐in‐the‐loop healthcare image information quality assessment and selection
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Smart healthcare applications cannot be separated from healthcare data analysis and the interactive interpretability between data and model. A human‐in‐the‐loop active learning approach is introduced to reduce the cost of healthcare data labelling by evaluating the information quality of unlabelled medical data and then screening the high ...
Yang Li, Sezai Ercisli
wiley +1 more source
Greedy vector quantization [PDF]
, 2014 We investigate the greedy version of the $L^p$-optimal vector quantization problem for an $\mathbb{R}^d$-valued random vector $X\!\in L^p$. We show the existence of a sequence $(a_N)_{N\ge 1}$ such that $a_N$ minimizes $a\mapsto\big \|\min_{1\le i\le N-1}
Luschgy, Harald, Pagès, Gilles
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Advanced Functional Materials, EarlyView.This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source
ADAPTIVE VECTOR QUANTIZATION FOR REINFORCEMENT LEARNING
IFAC Proceedings Volumes, 2002 Abstract Dynamic programming methods are capable of solving reinforcement learning problems, in which an agent must improve its behavior through trial-and-error interactions with a dynamic environment. However, these computational algorithms suffer from the curse of dimensionality (Bellman, 1957) that the number of computational operations ...
Lee, SK, Mak, KL, Lau, HYK
openaire +3 more sources
Generative Models for Crystalline Materials
Advanced Materials, EarlyView.Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni +15 more
wiley +1 more source
Advances in Mechanical Engineering, 2016 This article focuses on the design of a control system for intelligent prostheses. Learning vector quantization neural network–based model reference adaptive control method is employed to implement real-time trajectory tracking and damp torque control of
Jia-Qiang Yang, Lei Yang, Yuliang Ma
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