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Learning from Multiway Data: Simple and Efficient Tensor Regression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use TPG instead of Greedy | VAR (3) forecasting · Foursquare check-in | RMSE: 0.3639 -> 0.3580 | Helped |
| Use TPG instead of Greedy | VAR (3) forecasting · USHCN daily measurement | RMSE: 0.4389 -> 0.3872 | Helped |
| Use TPG instead of ADMM | VAR (3) forecasting · Foursquare check-in | RunTime: 445.41 -> 37.06 | Helped |
| Use TPG instead of ADMM | VAR (3) forecasting · USHCN daily measurement | RunTime: 6786 -> 144.43 | Helped |
| Use TPG instead of OLS | VAR (3) forecasting · Foursquare check-in | RMSE: 0.8277 -> 0.3580 | Helped |
| Use TPG instead of OLS | VAR (3) forecasting · USHCN daily measurement | RMSE: 1.4265 -> 0.3872 | Helped |
| Use count sketch instead of Gaussian or sparse random projection | TPG · Synthetic dataset | parameter estimation RMSE | Helped |
| Use TPG instead of MLMTL-C | Multi-linear multi-task learning · Restaurant & consumer dataset | mean squared error: 10 % - 25% more accurate | Helped |
| Use TPG instead of MLMTL-C | Multi-linear multi-task learning · Restaurant & consumer dataset | running time: at least 20 times faster | Helped |
Closest papers by meaning
- Low-Rank Tensor Transitions (LoRT) for Transferable Tensor Regression (ICML 2025 · similarity 0.87)
- Factor Augmented Tensor-on-Tensor Neural Networks (AAAI 2025 · similarity 0.87)
- High-Dimensional Tensor Regression With Oracle Properties (ICML 2025 · similarity 0.87)
- Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model (ICLR 2024 · similarity 0.86)
- Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts (NeurIPS 2024 · similarity 0.86)
- Large-scale Multi-view Tensor Clustering with Implicit Linear Kernels (CVPR 2025 · similarity 0.86)
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