Deep learning falls within the realm of artificial intelligence as a subset of machinelearning. It plays a crucial role in our everyday lives. The field of Deep learning has expanded significantly in recent years and...
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Prediction of next word is also known as language modeling and is an application of Natural Language Processing which helps in next word prediction. In the past, several studies employed various models to predict the ...
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Leaf diseases can have a considerable influence on crop production and food security. Therefore, it's crucial to detect and diagnose these diseases early to prevent their spread and minimize yield losses. Image pr...
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Bilevel optimization recently has received tremendous attention due to its great success in solving important machinelearning problems like meta learning, reinforcement learning, and hyperparameter optimization. Exte...
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Bilevel optimization recently has received tremendous attention due to its great success in solving important machinelearning problems like meta learning, reinforcement learning, and hyperparameter optimization. Extending single-agent training on bilevel problems to the decentralized setting is a natural generalization, and there has been a flurry of work studying decentralized bilevel optimization algorithms. However, it remains unknown how to design the distributed algorithm with sample complexity and convergence rate comparable to SGD for stochastic optimization, and at the same time without directly computing the exact Hessian or Jacobian matrices. In this paper we propose such an algorithm. More specifically, we propose a novel decentralized stochastic bilevel optimization (DSBO) algorithm that only requires first order stochastic oracle, Hessian-vector product and Jacobian-vector product oracle. The sample complexity of our algorithm matches the currently best known results for DSBO, while our algorithm does not require estimating the full Hessian and Jacobian matrices, thereby possessing to improved per-iteration complexity.
Heart disease and other forms of cardiovascular illness are considered as the leading causes of mortality, worldwide. There is a need to have a good method of diagnosing such disorders timely and accurately. Recent ye...
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The proceedings contain 54 papers. The special focus in this conference is on Soft computing and Signal Processing. The topics include: Stock Price Prediction Using LSTM, CNN and ANN;IoT-Based Smart Wearable Devices U...
ISBN:
(纸本)9789819984503
The proceedings contain 54 papers. The special focus in this conference is on Soft computing and Signal Processing. The topics include: Stock Price Prediction Using LSTM, CNN and ANN;IoT-Based Smart Wearable Devices Using Very Large Scale Integration (VLSI) Technology;plant Disease Detection and Classification Using Artificial Intelligence Approach;camera and Voice Control-Based Human–Computer Interaction Using machinelearning;optimal Crop Recommendation by Soil Extraction and Classification Techniques Using machinelearning;ioT-Based Smart Irrigation System in Aquaponics Using Ensemble machinelearning;Performance Evaluation of MFSK Techniques Under Various Fading Environments in Wireless Communication;prediction of Breast Cancer Using Feature Extraction-Based Methods;review and Design of Integrated Dashboard Model for Performance Measurements;anomaly Detection in Classroom Using Convolutional Neural Networks;Efficient VLSI Architectures of Multimode 2D FIR Filter Bank using Distributed Arithmetic Methodology;implementation of an Efficient Image Inpainting Algorithm using Optimization Techniques;A Systematic Study and Detailed Performance Assessment of SDN Controllers Across a Wide Range of Network Architectures;Classification and Localization of Objects Using Faster RCNN;an Image Processing Approach for Weed Detection Using Deep Convolutional Neural Network;detection of Leaf Black Sigatoka Disease in Enset Using Convolutional Neural Network;detecting Communities Using Network Embedding and Graph Clustering Approach;Deep learning Approaches-Based Brain Tumor Detection Using MRI Images—A Comprehensive Review;Predicting Crop Yield with AI—A Comparative Study of DL and ML Approaches;An Empirical Analysis of Lung Cancer Detection and Classification Using CT Images;trust and Secured Routing in Mobile Ad Hoc Network Using Block Chain.
Alzheimer's disease (AD) is a progressive neurological disorder characterised by aberrant behaviour, memory loss, and cognitive impairment. Electroencephalography (EEG) is an efficient method that provides valuabl...
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Food adulteration is common around the globe. To make sure to get high-quality food, and to identify the numerous adulterants in food items. The use of machinelearning and deep learning techniques in the detection of...
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This paper gives a thorough analysis of works on the subject of expert assessment of CPU burst time using various machinelearning algorithms. Knowing how long the CPU bursts for the processes will last is necessary f...
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The proceedings contain 54 papers. The special focus in this conference is on Soft computing and Signal Processing. The topics include: Stock Price Prediction Using LSTM, CNN and ANN;IoT-Based Smart Wearable Devices U...
ISBN:
(纸本)9789819986279
The proceedings contain 54 papers. The special focus in this conference is on Soft computing and Signal Processing. The topics include: Stock Price Prediction Using LSTM, CNN and ANN;IoT-Based Smart Wearable Devices Using Very Large Scale Integration (VLSI) Technology;plant Disease Detection and Classification Using Artificial Intelligence Approach;camera and Voice Control-Based Human–Computer Interaction Using machinelearning;optimal Crop Recommendation by Soil Extraction and Classification Techniques Using machinelearning;ioT-Based Smart Irrigation System in Aquaponics Using Ensemble machinelearning;Performance Evaluation of MFSK Techniques Under Various Fading Environments in Wireless Communication;prediction of Breast Cancer Using Feature Extraction-Based Methods;review and Design of Integrated Dashboard Model for Performance Measurements;anomaly Detection in Classroom Using Convolutional Neural Networks;Efficient VLSI Architectures of Multimode 2D FIR Filter Bank using Distributed Arithmetic Methodology;implementation of an Efficient Image Inpainting Algorithm using Optimization Techniques;A Systematic Study and Detailed Performance Assessment of SDN Controllers Across a Wide Range of Network Architectures;Classification and Localization of Objects Using Faster RCNN;an Image Processing Approach for Weed Detection Using Deep Convolutional Neural Network;detection of Leaf Black Sigatoka Disease in Enset Using Convolutional Neural Network;detecting Communities Using Network Embedding and Graph Clustering Approach;Deep learning Approaches-Based Brain Tumor Detection Using MRI Images—A Comprehensive Review;Predicting Crop Yield with AI—A Comparative Study of DL and ML Approaches;An Empirical Analysis of Lung Cancer Detection and Classification Using CT Images;trust and Secured Routing in Mobile Ad Hoc Network Using Block Chain.
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