Research map / Learning theory and algorithms / Submodular and game algorithms
Learning to Select Exogenous Events for Marked Temporal Point Process
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Club | time prediction MAE: 3.67±0.05 -> 3.57±0.15 | Helped |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Election | time prediction MAE: 8.50±0.01 -> 8.50±0.02 | No clear effect |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Series | time prediction MAE: 1.71±0.07 -> 1.15±0.05 | Helped |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Verdict | time prediction MAE: 2.27±0.00 -> 2.27±0.00 | No clear effect |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · BookOrder | time prediction MAE: 0.07±0.00 -> 0.07±0.00 | No clear effect |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Club | mark prediction error: 0.59±0.05 -> 0.60±0.11 | No clear effect |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Election | mark prediction error: 0.67±0.03 -> 0.43±0.02 | Helped |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · Verdict | mark prediction error: 0.71±0.01 -> 0.57±0.00 | Helped |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | RMTPP · BookOrder | mark prediction error: 0.49±0.00 -> 0.45±0.00 | Helped |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | THP · Club | time prediction MAE: 11.93±0.08 -> 11.51±0.07 | Helped |
| Filter selected exogenous events with TPP-Select instead of training on all events (superposition) | THP · Club | mark prediction error: 0.42±0.01 -> 0.36±0.01 | Helped |
| Use model-aware stochastic greedy selection (TPP-Select) instead of EM | exogenous event selection · Synthetic data | selection accuracy: 0.554 -> 0.806 | Helped |
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- Deep Continuous-Time State-Space Models for Marked Event Sequences (NeurIPS 2025 · similarity 0.87)
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