Monday September 19th | ||||||||
9 – 10:30 a.m. | 10:30 – 11 a.m. | 11 a.m. – 1 p.m. | 1 – 2:30 p.m. | 2:30 – 4:30 p.m. | 4:30 – 5 p.m. | 5 – 6:30 p.m. | ||
WTC | Auditorium | 243 – (W) eXplainable Knowledge Discovery | Coffee break | 243 – (W) eXplainable Knowledge Discovery | Lunch break | 243 – (W) eXplainable Knowledge Discovery | Coffee break | 243 – (W) eXplainable Knowledge Discovery |
Makalu | 280 – (W) Workshop on Trustworthy AI | 280 – (W) Workshop on Trustworthy AI | 254 – (W) PharML | 254 – (W) PharML | ||||
Kilimandjaro (1-2) |
149 – (W) ML & DM for Sports Analytics | 149 – (W) ML & DM for Sports Analytics | 149 – (W) ML & DM for Sports Analytics | 149 – (W) ML & DM for Sports Analytics | ||||
Kilimandjaro (3-4) |
286 – (W) AI in manufacturing | 286 – (W) AI in manufacturing | 260 (T) – Reward- Optimizing reco. | 260 (T) – Reward- Optimizing reco. | ||||
Mont-Blanc (1) |
183 (T) Multi- Target Prediction with DNN | 183 (T) Multi- Target Prediction with DNN | 156 – (W) MACLEAN | 156 – (W) MACLEAN | ||||
Mont-Blanc (2) |
270 – (W) Quantum Machine Learning | 270 – (W) Quantum Machine Learning | 277 – (W) Multi-Label Learning | 277 – (W) Multi-Label Learning | ||||
Everest | 198 – (T) Graph Embedding | 198 – (T) Graph Embedding | 273 – (W & T) Uplift Modeling | 273 – (W & T) Uplift Modeling | ||||
La Meije | 160 – (W) Active Inference | 160 – (W) Active Inference | ||||||
Minatec | Chrome 1 | Expedia Cross-brand Lodging Rec. |
Lung Cancer Survival Pred. |
PRINCE Out-of-distrib. Generalization |
PRINCE Out-of-distrib. Generalization |
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Palladium 2 | PhD forum | PhD forum | 205 – (W) MLfor Cybersecurity | 205 – (W) ML for Cybersecurity |
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Chrome 2+3 | 281 (W) – ITEM: IoT for Embedded ML | 281 (W) – ITEM: IoT for Embedded ML |
Friday September 23rd | |||||||
10 – 10:30 a.m. | 10:30 – 1:30 p.m. | 1:30 – 2:30 p.m. | 2:30 – 4:30 p.m. | 4:30 – 5 p.m. | 5 – 6:30 p.m. | ||
WTC | Auditorium | Coffee break | Industrial Day testimonies |
Lunch break | Industrial Day Confiance AI |
Coffee break | Industrial Day round table |
Makalu | 180 – (W) Learning on Temporal Data | 180 – (W) Learning on Temporal Data | 180 – (W) Learning on Temporal Data | ||||
Kilimandjaro (1-2) |
285 (W) – MIDAS | 285 (W) – MIDAS | 285 (W) – MIDAS | ||||
Kilimandjaro (3-4) |
288 (W & T) – Meta- Knowledge Transfer | 288 (W & T) – Meta- Knowledge Transfer | 288 (W & T) – Meta- Knowledge Transfer | ||||
Mont-Blanc (1) | 279 (W) – KDID 2022: 20th anniversary | 232 (W) – Interactive Adaptive Learning | 232 (W) – Interactive Adaptive Learning | ||||
Mont-Blanc (2) | 197 (W) – Data Science for Social Good | 305 (W) – Graph Quality | 305 (W) – Graph Quality | ||||
Everest | 306 (W) – Learning to Quantify: Methods and Applications | 282 (W) – New Frontiers in Mining Complex Data | 282 (W) – New Frontiers in Mining Complex Data | ||||
La Meije | 307 (T) – Sparse Neural Networks Training | 255 (W) Fair & effective Talent management | 255 (W) Fair & effective Talent management | ||||
Minatec | Palladium 2 | 275 (W) – Learning with Imbalanced Domain | 271 – (W) Teaching Machine Learning | 271 – (W) Teaching Machine Learning | |||
Chrome 2+3 | 269 (W) – MLG | 150 (T) methods for reproducible ML | 150 (T) methods for reproducible ML |