Research map / Probabilistic and scientific modeling / Molecules and proteins
Nonparametric Decomposition of Sparse Tensors
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add sociability (DP weight) to embeddings, i.e., NEST-1 vs GPTF | NEST-1 · Alog, MovieLens, SG (entry value prediction) | MSE/MAE | Helped |
| Use multiple overlapping sociabilities (NEST-2) instead of NEST-1 (ablation) | NEST-2 · Entry value prediction (Alog, MovieLens, SG) | MSE/MAE | Helped |
| Use NEST sparse tensor process (DP/GEM sampling of indices) vs exchangeable CP/GP models | NEST-1 and NEST-2 · Entry index prediction (Alog, MovieLens) | AUC | Helped |
| Sparse-tensor NEST vs dense exchangeable models in tensor sampling | NEST-1, NEST-2 · Synthetic tensor sampling | #Entries/Tensor Size | Helped |
Closest papers by meaning
- Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes (ICML 2022 · similarity 0.94)
- Doubly Decomposing Nonparametric Tensor Regression (ICML 2016 · similarity 0.91)
- Efficient Nonparametric Tensor Decomposition for Binary and Count Data (AAAI 2024 · similarity 0.91)
- Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition (ICML 2022 · similarity 0.90)
- Boosted Sparse and Low-Rank Tensor Regression (NeurIPS 2018 · similarity 0.90)
- Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts (NeurIPS 2024 · similarity 0.88)
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