Research map / Learning theory and algorithms / Matrix and tensor methods
A Greedy Approach for Budgeted Maximum Inner Product Search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Greedy-MIPS candidate screening instead of PCA-MIPS, LSH-MIPS, or Diamond-MSIPS | MIPS on Yahoo-Music · Yahoo-Music, k=200, similar 200x speedup | top-5 precision: p_5=70%; none ... can achieve a p_5 > 10% | Helped |
| Replace the original screening procedure with the improved screening procedure that avoids heap updates for already-selected candidates (ablation) | Greedy-MIPS · Budgeted MIPS | candidate-screening time complexity: O(Bk log k) -> O(Bk) | Helped |
| Use a selection tree instead of a max-heap (ablation) | Greedy-MIPS · Netflix and Yahoo-Music | runtime | No clear effect |
| Use the original screening procedure instead of the improved screening procedure (ablation) | Greedy-MIPS · Netflix and Yahoo-Music | runtime | Hurt |
| Use a selection tree instead of a max-heap (ablation) | Greedy-MIPS · Budgeted MIPS | runtime: O(k) ... O(1) ... O(log k) | Helped |
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