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High Dimensional Data Analysis

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High Dimensional Data Analysis

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Research Frontiers in Tensor Decomposition and Multi-way Analysis

Research on factorization methods for higher-order tensors including Tucker decomposition and CP decomposition for analyzing multi-dimensional data.

Latent Structure Discovery in High-Order Tensors
Sparse Tensor Decomposition Across Massive Datasets
Non-Convex Optimization in Multilinear Factor Analysis
Temporal Dynamics in Streaming Tensor Decomposition
Identifiability Frontiers in Coupled Tensor Factorization
Interpretable Tensor Networks for Complex Data Systems
Robust Decomposition Under Noise and Missing Data
Scalability Limits in Higher-Order Dimension Reduction
Tensor Geometry and Algebraic Constraint Discovery
Cross-Modal Tensor Integration in Heterogeneous Domains

All High Dimensional Data Analysis PhD categories