
Broad Learning System Based on Maximum Correntropy Criterion
As an effective and efficient discriminative learning method, Broad Lear...
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MultiView MultiInstance MultiLabel Learning based on Collaborative Matrix Factorization
Multiview Multiinstance Multilabel Learning(M3L) deals with complex o...
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MultiView Multiple Clusterings using Deep Matrix Factorization
Multiview clustering aims at integrating complementary information from...
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Partial Multilabel Learning with Label and Feature Collaboration
Partial multilabel learning (PML) models the scenario where each traini...
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ActiveHNE: Active Heterogeneous Network Embedding
Heterogeneous network embedding (HNE) is a challenging task due to the d...
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Multiple Independent Subspace Clusterings
Multiple clustering aims at discovering diverse ways of organizing data ...
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MultiView Multiple Clustering
Multiple clustering aims at exploring alternative clusterings to organiz...
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Weaklypaired CrossModal Hashing
Hashing has been widely adopted for largescale data retrieval in many d...
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Deep Incomplete MultiView Multiple Clusterings
Multiview clustering aims at exploiting information from multiple heter...
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Generalization of DempsterShafer theory: A complex belief function
DempsterShafer evidence theory has been widely used in various fields o...
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Rankingbased Deep Crossmodal Hashing
Crossmodal hashing has been receiving increasing interests for its low ...
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AttentionAware Answers of the Crowd
Crowdsourcing is a relatively economic and efficient solution to collect...
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A DEMATELBased Completion Method for Incomplete Pairwise Comparison Matrix in AHP
Pairwise comparison matrix as a crucial component of AHP, presents the p...
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Multiscale probability transformation of basic probability assignment
Decision making is still an open issue in the application of DempsterSh...
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A new combination approach based on improved evidence distance
DempsterShafer evidence theory is a powerful tool in information fusion...
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Generalized Evidence Theory
Conflict management is still an open issue in the application of Dempste...
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Distance function of D numbers
DempsterShafer theory is widely applied in uncertainty modelling and kn...
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Modeling contaminant intrusion in water distribution networks based on D numbers
Efficient modeling on uncertain information plays an important role in e...
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DCFPR: D numbers extended consistent fuzzy preference relations
How to express an expert's or a decision maker's preference for alternat...
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Parameter estimation based on intervalvalued belief structures
Parameter estimation based on uncertain data represented as belief struc...
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Quantifying patterns of research interest evolution
Our quantitative understanding of how scientists choose and shift their ...
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Diffusion Adaptation Framework for Compressive Sensing Reconstruction
Compressive sensing(CS) has drawn much attention in recent years due to ...
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Maximum Total Correntropy Diffusion Adaptation over Networks with Noisy Links
Distributed estimation over networks draws much attraction in recent yea...
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SAIGA: A Multiagent Reinforcement Learning Method Towards Socially Optimal Outcomes
In multiagent environments, the capability of learning is important for ...
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MedShare: Medical Resource Sharing among Autonomous Healthcare Providers
Legacy Electronic Health Records (EHRs) systems were not developed with ...
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Trajectory Design for Distributed Estimation in UAV Enabled Wireless Sensor Network
In this paper, we study an unmanned aerial vehicle(UAV)enabled wireless...
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Multisensor data fusion based on a generalised belief divergence measure
Multisensor data fusion technology plays an important role in real appl...
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On Solving Ambiguity Resolution with Robust Chinese Remainder Theorem for Multiple Numbers
Chinese Remainder Theorem (CRT) is a powerful approach to solve ambiguit...
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Parameter Synthesis Problems for one parametric clock Timed Automata
In this paper, we study the parameter synthesis problem for a class of p...
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CoherenceBased Performance Guarantee of Regularized ℓ_1Norm Minimization and Beyond
In this paper, we consider recovering the signal x∈R^n from its few nois...
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Collaboration based MultiLabel Learning
It is wellknown that exploiting label correlations is crucially importa...
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Deterministic Analysis of Weighted BPDN With Partially Known Support Information
In this paper, with the aid of the powerful Restricted Isometry Constant...
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From Coprime to the Diophantine Equation Based Sparse Sensing in Complex Waveforms
For frequency estimation, the coprime sampling tells that in time domai...
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A SeqtoSeq Transformer Premised Temporal Convolutional Network for Chinese Word Segmentation
The prevalent approaches of Chinese word segmentation task almost rely o...
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Tensor Restricted Isometry Property Analysis For a Large Class of Random Measurement Ensembles
In previous work, theoretical analysis based on the tensor Restricted Is...
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RIPbased performance guarantee for lowtubalrank tensor recovery
The essential task of multidimensional data analysis focuses on the ten...
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Evidential distance measure in complex belief function theory
In this paper, an evidential distance measure is proposed which can meas...
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Generalized Belief Function: A new concept for uncertainty modelling and processing
In this paper, we generalize the belief function on complex plane from a...
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China may need to support more small teams in scientific research
Modern science is dominated by scientific productions from teams. Large ...
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An analysis of noise folding for lowrank matrix recovery
Previous work regarding lowrank matrix recovery has concentrated on the...
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The block mutual coherence property condition for signal recovery
Compressed sensing shows that a sparse signal can stably be recovered fr...
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The perturbation analysis of nonconvex lowrank matrix robust recovery
In this paper, we bring forward a completely perturbed nonconvex Schatte...
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The highorder block RIP for nonconvex blocksparse compressed sensing
This paper concentrates on the recovery of blocksparse signals, which i...
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Measuring similarity in cooccurrence data using egonetworks
The cooccurrence association is widely observed in many empirical data....
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Southwest University