Open-world assumption

The Open World AssumptionПодробнее

[rfp0242] Rethinking Cross-Domain Sequential Recommendation under Open-World AssumptionsПодробнее

Tunable Hybrid Proposal Networks for the Open WorldПодробнее

NDSS 2023 - Anomaly Detection in the Open World: Normality Shift Detection, Explanation, and Adap...Подробнее

Introduction to Logic Programming and Open World ReasoningПодробнее

Introducing PyReason: Open world temporal logicПодробнее

USENIX Security '22 - FOAP: Fine-Grained Open-World Android App FingerprintingПодробнее

T5: Completeness, Recall, and Negation in Open-World Knowledge BasesПодробнее

OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak SupervisionПодробнее

[Open World Lifelong Learning Course] Lecture #11: Continual reinforcement learning - Massimo CacciaПодробнее

[Open World Lifelong Learning Course] Lecture #10: The role of soft + hardware & PyTorch AvalancheПодробнее

[Open World Lifelong Learning Course] Lecture #9: order, difficulty & curriculum learning.Подробнее

[Open World Lifelong Learning Course] Lecture #8: Learning & prediction in presence of the unknownПодробнее

[Open World Lifelong Learning Course] Lecture #7: Evaluation - what to measure & general challengesПодробнее

[Open World Lifelong Learning Course] Lecture #6: Modular/dynamic (neural) architecturesПодробнее

[Open World Lifelong Learning Course] Lecture #5: Active learning - querying future dataПодробнее

[Open World Lifelong Learning Course] Lecture #3: knowledge retention, optimization & forgettingПодробнее

[Open World Lifelong Learning Course] Lecture #2: knowledge transfer, adaptation, continual learningПодробнее

DL: Some ExamplesПодробнее

Closed World AssumptionПодробнее