Data-driven model reduction library with an emphasis on large scale parallelism and linear subspace methods
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Updated
Nov 7, 2024 - C++
Data-driven model reduction library with an emphasis on large scale parallelism and linear subspace methods
Subspace Graph Physics
Data Augmented Flatness-aware Gradient Projection for Continual Learning. ICCV, 2023.
A novel dynamic learning strategy that overcomes the empirical search of an optimal number of subspace learners in multiple metric learners.
Code for the ICLR2022 paper on Subspace Regularization for few-shot class incremental image classification
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
Multimodal Subspace Support Vector Data Description
[IEEE TSP 2021] “Robust Subspace Tracking with Missing Data and Outliers: Novel Algorithm with Convergence Guarantee”. IEEE Transactions on Signal Processing, 2021.
OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1
Dimension Reduction and Estimation Methods
Subspace Support Vector Data Description
Ellipsoidal Subspace Support Vector Data Description
MATLAB implementation of "Federated Over-Air Subspace Tracking from Incomplete and Corrupted Data", IEEE Transactions on Signal Processing, Jun 2022.
We implement some sparse representation based face recognition algorithms here, including LRC, SRC, CRC, ESRC and etc.
We use self-expressive layer to learn the affinity matrix of the hidden space of a generator, and we found subspace in GAN. Also we propsed a subspace-based high-fidelity GAN inversion model.
Streaming, Memory-Limited, r-truncated SVD Revisited!
IMTSL - Incremental and Multi-feature Tensor Subspace Learning
The code for prototype selection and instance ranking using matrix decomposition and subspace learning
source code for SDSPCAAN
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