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Robust multiview spectral clustering via cooperative manifold and low rank representation induced
This paper proposes a novel multiview low-rank clustering method to learn robust multiview clustering from two different data structures, unlike...
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An Evolutionary Multiobjective Optimization Algorithm Based on Manifold Learning
Multi-objective optimization problem is widespread in the real world. However, plenty of typical evolutionary multi-objective optimization (EMO)...
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Robust autonomous landing of UAVs in non-cooperative environments based on comprehensive terrain understanding
Autonomous landing in non-cooperative environments is a key step toward full autonomy of unmanned aerial vehicles (UAVs). Existing studies have...
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A Monte Carlo manifold spectral clustering algorithm based on emotional preference and migratory behavior
Inspired by various behaviors of creatures in nature, numerous efficient bionic algorithms are designed for dealing with complex clustering problems....
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Low-rank tensor multi-view subspace clustering via cooperative regularization
In order to explore the importance of the hypergraph regularization and the Tikhonov regularization in multi-view clustering, this paper proposes a...
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Reachability Analysis to Track Non-cooperative Satellite in Cislunar Regime
Space Domain Awareness (SDA) architectures must adapt to overcome the challenges present in cislunar space. Dynamical systems theory provides tools...
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Multi-layer manifold learning with feature selection
Many fundamental problems in machine learning require some form of dimensionality reduction. To this end, two different strategies were used:...
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Monocular 6-DoF Pose Estimation for Non-cooperative Spacecrafts Using Riemannian Regression Network
As it is closely related to spacecraft in-orbit servicing, space debris removal, and other proximity operations, on-board 6-DoF pose estimation of...
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Joint feature and instance selection using manifold data criteria: application to image classification
In many pattern recognition applications feature selection and instance selection can be used as two data preprocessing methods that aim at reducing...
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Multi-layer linear embedding with feature subset selection
Many fundamental problems in machine learning require some form of dimensionality reduction. To this end, two different strategies were used:...
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‘The Discipline of Steel’: Technical Knowledge in the Coordinative Practices of Steelmaking
This is a study of the cooperative work of making steel in a contemporary steel plant. The study is, first of all, a study of the coordinative...
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Sliding modes of high codimension in piecewise-smooth dynamical systems
We consider piecewise-smooth dynamical systems, i.e., systems of ordinary differential equations switching between different sets of equations on...
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Revelation of hidden 2D atmospheric turbulence strength fields from turbulence effects in infrared imaging
Turbulence exists widely in the natural atmosphere and in industrial fluids. Strong randomness, anisotropy and mixing of multiple-scale eddies...
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Aligning artificial intelligence with moral intuitions: an intuitionist approach to the alignment problem
As artificial intelligence (AI) continues to advance, one key challenge is ensuring that AI aligns with certain values. However, in the current...
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InterGen: Diffusion-Based Multi-human Motion Generation Under Complex Interactions
We have recently seen tremendous progress in diffusion advances for generating realistic human motions. Yet, they largely disregard the multi-human...
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Investigating Air Pollution Dynamics in Ho Chi Minh City: A Spatiotemporal Study Leveraging XAI-SHAP Clustering Methodology
Air pollution poses an urgent challenge to public health and ecosystems, particularly in rapidly urbanizing regions. Despite the severity of this...
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AutoMix: Mixup Networks for Sample Interpolation via Cooperative Barycenter Learning
This paper proposes new ways of sample mixing by thinking of the process as generation of barycenter in a metric space for data augmentation. First,...
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Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values
Shapley values have achieved great popularity in explainable artificial intelligence. However, with standard sampling methods, resulting feature...
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Shape generation via learning an adaptive multimodal prior
Significant interest and progress have been drawn to the recent advancements in image creation using deep generative model, but the field of...
