Filters








46,266 Hits in 3.2 sec

On Estimating the Training Cost of Conversational Recommendation Systems [article]

Stefanos Antaris, Dimitrios Rafailidis, Mohammad Aliannejadi
2020 arXiv   pre-print
However, conversational recommendation systems are based on complex neural architectures, thus the training cost of such models is high.  ...  Conversational recommendation systems have recently gain a lot of attention, as users can continuously interact with the system over multiple conversational turns.  ...  Various neural architectures have been introduced for conversation recommendation. For example, Kumar et al.  ... 
arXiv:2011.05302v1 fatcat:kr7ua6ipn5fhrgkqdydwe426oe

Adaptive Neural Fuzzy Inference System for Employability Assessment

Rajani Kumari, Vivek Kumar Sharma, Sandeep Kumar
2014 International Journal of Computer Applications Technology and Research  
The proposed system is named as Adaptive Neural Fuzzy Inference System for Employability Assessment (ANFISEA).  ...  This paper introduced a new adaptive neural fuzzy inference system for assessment of employability with the help of some neuro fuzzy rules.  ...  ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM FOR EMPLOYABILITY ASSESSMENT This paper introduced an innovative adaptive neural fuzzy inference system for employability with the help of some neuro fuzzy rules.  ... 
doi:10.7753/ijcatr0303.1006 fatcat:kru6yts3srfl5eohrsul6r6vzy

Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search [article]

Lei Chen, Fajie Yuan, Jiaxi Yang, Min Yang, Chengming Li
2021 arXiv   pre-print
diverse neural architectures for sequential recommender models under different recommendation scenes.  ...  Naturally, we argue that compressing the heavy recommendation models into middle- or light- weight neural networks is of great importance for practical production systems.  ...  AdaRec distills the knowledge of a teacher model into a student model adaptively according to the recommendation scene based on differentiable Neural Architecture Search (NAS) [11] , [12] , [13] .  ... 
arXiv:2107.07173v1 fatcat:po2uvmxppje5pgyppfafnqgkia

Adaptive data sensing rate in ad-hoc sensor networks for autonomous transport application

Xinwei Wang, A Jabbari, R Jedermann, R Laur, W Lang
2010 2010 13th International Conference on Information Fusion  
A novel algorithm for adaptive control of the data sensing rate in wireless ad-hoc sensor networks (WSN) is presented.  ...  The algorithm of adaptive sensing rate is tested in a simulation environment and implemented in a refrigerator truck for a food transport purpose.  ...  The neural network architecture in Fig. 2 is used to evaluate a single parameter. However, this structure is able to be extended to form more complex architectures for two different parameters.  ... 
doi:10.1109/icif.2010.5711911 fatcat:hhlq3geu2jhpllad5thaerhmfy

Development of End – to – End Encoder - Decoder Model Applying Voice Recognition System in Different Channels

2019 International journal of recent technology and engineering  
Hence, the study finds the result of voice recognition which is most effective for adaptation.  ...  ) – based system and lead to multiple experimental results.  ...  Also, implementation of speaker adaptation is recommended in multichannel ASR system.  ... 
doi:10.35940/ijrte.b1267.0982s1119 fatcat:shkpdi6xc5gejkncmqa4hcqu3q

Intelligent Control Algorithms in Power Industry

Vyacheslav V. Potekhin, Dmitry N. Pantyukhov, Dmitrii V. Mikheev
2017 EAI Endorsed Transactions on Energy Web  
The article considers a solution the problem of creating energy technologies for autonomous decentralized energy supply, using intelligent automated control systems.  ...  This type of neural networks can be easily implemented, the structure of neural network allows the easy way to describe given architecture.  ...  This type of neural networks can be easily implemented, the structure of neural network allows the easy way to describe given architecture.  ... 
doi:10.4108/eai.11-7-2017.152766 fatcat:v7xa3luu5faezor4rb4se5zrmu

Intelligent Control Algorithms in Power Industry

Vyacheslav V. Potekhin, Dmitry N. Pantyukhov, Dmitrii V. Mikheev
2017 EAI Endorsed Transactions on Energy Web  
The article considers a solution the problem of creating energy technologies for autonomous decentralized energy supply, using intelligent automated control systems.  ...  This type of neural networks can be easily implemented, the structure of neural network allows the easy way to describe given architecture.  ...  This type of neural networks can be easily implemented, the structure of neural network allows the easy way to describe given architecture.  ... 
doi:10.4108/eai.14-7-2017.152894 fatcat:36dy2pzsbnfsdilvrjehpijvyq

Neural network architecture for control

A. Guez, J.L. Eilbert, M. Kam
1988 Control Systems Magazine  
The utilization of neural networks for adaptive control offers definite speed advantages over traditional approaches for very large scale systems.  ...  Introduction A computing architecture for adaptive control based on computational features of nonlinear neural networks is proposed.  ...  Figure 1 illustrates the proposed neuromorphic adaptation architecture for control.  ... 
doi:10.1109/37.1869 fatcat:3s2qcxqmafc6fmrljj2ktx5cmu

Matters of Neural Network Repository Designing for Analyzing and Predicting of Spatial Processes

Stanislav A. Yamashkin, Anatoliy A. Yamashkin, Ekaterina O. Yamashkina, Anastasiya A. Kamaeva
2021 International Journal of Advanced Computer Science and Applications  
The issues of architecture development and software implementation of a repository of deep neural network models for spatial data analysis are considered, based on a new ontological model, which makes  ...  The authors have shown that for organizing a repository of deep neural network models, it is advisable to use a scientifically grounded set of database management systems integrated into a multi-model  ...  regions. 10) Development of a recommendation system for the selection and configuration of deep neural network models.  ... 
doi:10.14569/ijacsa.2021.0120503 fatcat:jyvlustezvcdphgfyb4f3xgeji

CHAMELEON: A Deep Learning Meta-Architecture for News Recommender Systems [Phd. Thesis] [article]

Gabriel de Souza Pereira Moreira
2019 arXiv   pre-print
It consists of a modular reference architecture which can be instantiated using different neural building blocks.  ...  Recommender Systems (RS) have became a popular research topic and, since 2016, Deep Learning methods and techniques have been increasingly explored in this area.  ...  ., 2017b) , it is proposed a neural architecture based on DSSM for news recommendation.  ... 
arXiv:2001.04831v1 fatcat:x2k3u26i4jebzjlesswnncfepq

Adaptive Tuning Algorithm for Performance tuning of Database Management System [article]

S. F. Rodd, U. P. Kulkarni
2010 arXiv   pre-print
As neural networks have the ability to adapt to dynamically changing inputs and also their ability to learn makes them ideal candidates for employing them for tuning purpose.  ...  Performance tuning of Database Management Systems(DBMS) is both complex and challenging as it involves identifying and altering several key performance tuning parameters.  ...  D.A.Kulkarni for scruitimizing the paper and for his valueable suggestions. Special thanks to Prof. Santosh Saraf for his help in learning Neural Network implementation in MATLAB.  ... 
arXiv:1005.0972v1 fatcat:pkeqk4sxordkfgbgdbs3dzycdi

Agent-Augmented Co-Space: Toward Merging of Real World and Cyberspace [chapter]

Ah-Hwee Tan, Yilin Kang
2010 Lecture Notes in Computer Science  
Following the notion of embodied intelligence, we propose to develop cognitive agents, based on a family of self-organizing neural models, known as fusion Adaptive Resonance Theory (fusion ART).  ...  This paper will begin with a brief review of this emerging field of work related to agents in virtual worlds and integrated cognitive architectures.  ...  with a reinforcement learning system known as Temporal Difference -Fusion Architecture for Learning and Cognition (TD-FALCON).  ... 
doi:10.1007/978-3-642-16576-4_22 fatcat:tw3b6hjzpjfedmmet527vjpfoi

Recent Advances in Heterogeneous Relation Learning for Recommendation [article]

Chao Huang
2021 arXiv   pre-print
We discuss the learning approaches in each category, such as matrix factorization, attention mechanism and graph neural networks, for effectively distilling heterogeneous contextual information.  ...  To address this problem, recent research developments can fall into three major lines: social recommendation, knowledge graph-enhanced recommender system, and multi-behavior recommendation.  ...  Graph-based Multi-Behavior Recommender Systems. The second type of multi-behavior recommender systems are built upon the graph neural architectures.  ... 
arXiv:2110.03455v1 fatcat:fskj4qdsibfnxefklazdli3tgu

News Session-Based Recommendations using Deep Neural Networks

Gabriel de Souza Pereira Moreira, Felipe Ferreira, Adilson Marques da Cunha
2018 Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems - DLRS 2018  
In this paper, it is proposed an instantiation of the CHAMELEON -- a Deep Learning Meta-Architecture for News Recommender Systems.  ...  Some promising results have been recently achieved by the usage of Deep Learning techniques on Recommender Systems, specially for item's feature extraction and for session-based recommendations with Recurrent  ...  ACKNOWLEDGMENTS The authors would like to thank Globo.com for providing context on its challenges for large-scale news recommender systems and for sharing a dataset to make those experiments possible.  ... 
doi:10.1145/3270323.3270328 dblp:conf/recsys/MoreiraFC18 fatcat:rurrhe35b5dhjl7xiu2j4cdg2i

Physical Exercise Recommendation and Success Prediction Using Interconnected Recurrent Neural Networks [article]

Arash Mahyari, Peter Pirolli
2021 arXiv   pre-print
The system, consisting of two inter-connected recurrent neural networks (RNNs), uses the history of workouts to recommend the next workout activity for each individual.  ...  In this paper, we propose an exercise recommendation system that also predicts individual success rates.  ...  In [12] , a multi-stack recurrent neural network (RNN) architecture is used to develop a recommendation system to suggest businesses in Yelp based on their reviews. Wu et al.  ... 
arXiv:2010.00482v2 fatcat:5n3ddw4mbbgingdck5xefgs4pi
« Previous Showing results 1 — 15 out of 46,266 results