conftrace_

low-rank approximation

323 papers

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Also known as

LORA

Co-occurring keywords

model compression (3302) matrix factorization (529) matrix completion (356) tensor decomposition (375) singular value decomposition (222) matrix approximation (89) dimensionality reduction (720) tensor completion (64) kernel methods (1097) convex optimization (1321)

Papers

Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining AISTATS 2023
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions NIPS 2023
Group SLOPE Penalized Low-Rank Tensor Regression JMLR 2023
Efficient Structure-preserving Support Tensor Train Machine JMLR 2023
Efficient Low-rank Backpropagation for Vision Transformer Adaptation NIPS 2023
Kissing to Find a Match: Efficient Low-Rank Permutation Representation NIPS 2023
Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms NIPS 2023
Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations COLT 2023
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily NIPS 2023
Compressing Transformers: Features Are Low-Rank, but Weights Are Not! AAAI 2023
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks NIPS 2023
SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture Search WACV 2023
Eigencontours: Novel Contour Descriptors Based on Low-Rank Approximation CVPR 2022
NysADMM: faster composite convex optimization via low-rank approximation ICML 2022
Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences NAACL 2022
Dynamic Nonlinear Matrix Completion for Time-Varying Data Imputation AAAI 2022
Low-rank Optimal Transport: Approximation, Statistics and Debiasing NIPS 2022
Recovering shared structure from multiple networks with unknown edge distributions JMLR 2022
Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks NIPS 2022
Compressible-composable NeRF via Rank-residual Decomposition NIPS 2022
Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations NIPS 2022
How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022
Improved analysis of randomized SVD for top-eigenvector approximation AISTATS 2022
Paramixer: Parameterizing Mixing Links in Sparse Factors Works Better Than Dot-Product Self-Attention CVPR 2022
Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee JMLR 2022