Research map / Learning theory and algorithms / Matrix and tensor methods
On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use TT-RALS instead of TCAM-TT | Electricity data completion · Electricity data, K=5 | Error: 0.219 -> 0.219 | No clear effect |
| Use TT-RALS instead of TCAM-TT | Electricity data completion · Electricity data, K=7 | Error: 0.928 -> 0.928 | No clear effect |
| Use TT-RALS instead of TCAM-TT | Electricity data completion · Electricity data, K=8 | Error: 0.928 -> 0.928 | No clear effect |
| Use TT-RALS instead of TCAM-TT | Electricity data completion · Electricity data, K=7 | Time (seconds): 27.497 -> 4.726 | Helped |
| Use TT-RALS instead of TCAM-TT | Electricity data completion · Electricity data, K=8 | Time (seconds): 146.651 -> 7.654 | Helped |
| Use TT-RALS instead of TT-ADMM | Electricity data completion · Electricity data, K=5 | Time (seconds): 0.289 -> 4.644 | Hurt |
| Use TT-RALS for higher-order completion | Electricity data completion · Electricity data, K=10 | Time (seconds) | Helped |
Closest papers by meaning
- Fast Tensor Completion via Approximate Richardson Iteration (ICML 2025 · similarity 0.91)
- Efficient Leverage Score Sampling for Tensor Train Decomposition (NeurIPS 2024 · similarity 0.90)
- Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion (AAAI 2019 · similarity 0.90)
- Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion (AAAI 2021 · similarity 0.90)
- Constructive TT-representation of the tensors given as index interaction functions with applications (ICLR 2023 · similarity 0.90)
- Beyond Lazy Training for Over-parameterized Tensor Decomposition (NeurIPS 2020 · similarity 0.89)
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