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Revisiting data reduction for boolean matrix factorization algorithms based on formal concept analysis
Boolean Matrix Factorization (BMF) helps unveil hidden patterns in boolean datasets and is a powerful tool in machine learning. However, when dealing...
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Using Incremental Algorithm in Hybrid Recommender System Combined Sentiment Analysis
Beside the problem how to improve hybrid system combine sentiment analysis, develo** incremental algorithms become an interesting research in...
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An initialization method to improve the training time of matrix factorization algorithm for fast recommendation
Recommendation systems are successful personalizing tools and information filtering in web. One of the most important recommendation methods is...
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Cross-domain incremental recommendation system based on meta learning
With e-commerce gradually replacing traditional retailers and the ability to analyze consumer behavioral data to recommend related products, the...
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Adaptive factorization rank selection-based NMF and its application in tumor recognition
The nonnegative matrix factorization (NMF) has been widely used because it can accomplish both feature representation learning and dimension...
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Accelerated construction of projection-based reduced-order models via incremental approaches
We present an accelerated greedy strategy for training of projection-based reduced-order models for parametric steady and unsteady partial...
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Projection continuation for minimal coordinate set formulation and singularity detection of redundantly constrained system dynamics
The formulation of (possibly redundantly) constrained system dynamics using coordinate projection onto a subspace locally tangent to the constraint...
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Introducing PIVOT: Predictive Incremental Variable Ordering Tactic for Efficient Belief Space Planning
Belief Space Planning (BSP) is a fundamental technique in artificial intelligence and robotics, which is widely used in the solution of problems such...
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Bayesian incremental inference update by re-using calculations from belief space planning: a new paradigm
Inference and decision making under uncertainty are key processes in every autonomous system and numerous robotic problems. In recent years, the...
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A dynamic hierarchical incremental learning-based supervised clustering for data stream with considering concept drift
Clustering analysis is an important data mining method for data stream. Data stream clustering is a branch of clustering in which the patterns are...
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A hybrid approach to three-way conversational recommendation
Conversational recommendation is ubiquitous in e-commerce, while three-way recommendation provides friendly choices for service providers and users....
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A projection continuation approach for minimal coordinate set constrained dynamics
The formulation of constrained system dynamics using coordinate projection onto a subspace locally tangent to the constraint manifold is revisited...
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Characterizing Marginalization and Incremental Operations on the Bayes Tree
Perception systems for autonomy are most useful if they can operate within limited/predictable computing resources. Existing algorithms in robot...
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Deep Learning Model Optimization
This chapter reviews recent work on compressing and accelerating deep neural networks, which has attracted much attention from the deep learning...
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An efficient Galerkin averaging-incremental harmonic balance method for nonlinear dynamic analysis of rigid multibody systems governed by differential–algebraic equations
An efficient Galerkin averaging-incremental harmonic balance (EGA-IHB) method is developed for steady-state nonlinear dynamic analysis of index-3...
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Incremental nonnegative matrix factorization based on correlation and graph regularization for matrix completion
Matrix factorization is widely used in recommendation systems, text mining, face recognition and computer vision. As one of the most popular methods,...
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Approaching the cold-start problem using community detection based alternating least square factorization in recommendation systems
In e-commerce, the opinion of users about products and the reviews are identified using recommender systems. Collaborative filtering techniques are...
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Cooperative Localization of Satellite Cluster via Factor Graphs Theory
In this paper, a new factor graph-based approach is presented to achieve the cooperative localization of the satellite cluster by using both multiple...
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Object Motion Detection in Video by Fusion of RPCA and NMF Decompositions
In this paper two new schemes are proposed for fusion of the results from video decomposition by Robust Principal Component Analysis and Non-negative...
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A Recommender Engine for Scientific Paper Peer-Reviewing System
The peer-reviewing process governs the quality of scientific researches by justifying answers to some meaningful research questions and concluding...