Long-term series forecasting with Query Selector -- efficient model of sparse attention
2021-07-19Code Available1· sign in to hype
Jacek Klimek, Jakub Klimek, Witold Kraskiewicz, Mateusz Topolewski
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ReproduceCode
- github.com/moraieu/query-selectorOfficialIn paperpytorch★ 74
- github.com/moraieu/query-selector-classificationpytorch★ 2
Abstract
Various modifications of TRANSFORMER were recently used to solve time-series forecasting problem. We propose Query Selector - an efficient, deterministic algorithm for sparse attention matrix. Experiments show it achieves state-of-the art results on ETT, Helpdesk and BPI'12 datasets.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| BPI challenge '12 | QuerySelector | Accuracy | 0.79 | — | Unverified |
| Helpdesk | QuerySelector | Accuracy | 0.74 | — | Unverified |