alternating least square

Open Problem: How much overparametrization is needed for ALS in tensor decomposition? COLT 2026 Tensor Network Based Feature Learning Model AISTATS 2025 Efficient Leverage Score Sampling for Tensor Train Decomposition NeurIPS 2024 Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms NeurIPS 2024 Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation ICML 2024 ATD: Augmenting CP Tensor Decomposition by Self Supervision NeurIPS 2022 Fused Orthogonal Alternating Least Squares for Tensor Clustering NeurIPS 2022 More Efficient Sampling for Tensor Decomposition With Worst-Case Guarantees ICML 2022 Subquadratic Kronecker Regression with Applications to Tensor Decomposition NeurIPS 2022 A Sampling-Based Method for Tensor Ring Decomposition ICML 2021 Fast and accurate randomized algorithms for low-rank tensor decompositions NeurIPS 2021 On the Faster Alternating Least-Squares for CCA AISTATS 2021 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates ICML 2021 Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition ICML 2020 Scalable Probabilistic Matrix Factorization with Graph-Based Priors AAAI 2020 Practical Coding Function Design for Time-Of-Flight Imaging CVPR 2019 Smooth neighborhood recommender systems JMLR 2019 Tensorial Change Analysis Using Probabilistic Tensor Regression AAAI 2019 Towards Practical Alternating Least-Squares for CCA NeurIPS 2019 Improving Implicit Recommender Systems with View Data IJCAI 2018 Statistical mechanics of low-rank tensor decomposition NeurIPS 2018 Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use ICML 2017 Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis NeurIPS 2016 SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling NeurIPS 2016 Fast and Guaranteed Tensor Decomposition via Sketching NeurIPS 2015