Sequence Modeling
نمذجة التتابعات
مهمة تعلّم التوزيع الاحتمالي فوق تتابعات البيانات — كالنصوص أو الموسيقى أو إشارات الكلام — بحيث يمكن للنموذج التنبؤ بالعنصر التالي بناءً على ما سبقه.
The task of learning a probability distribution over data sequences — such as text, music, or speech signals — so the model can predict the next element given the preceding elements.
Also translated asنمذجة المتسلسلات
First appears in this corpus in: Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling (2014)
Appears in these papers
- BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer2019in the sky ✦
- Decision Transformer: Reinforcement Learning via Sequence Modeling2021in the sky ✦
- Decision Transformer: Reinforcement Learning via Sequence Modeling2021in the sky ✦
- Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling2014in the sky ✦
- Efficiently Modeling Long Sequences with Structured State Spaces2022in the sky ✦
- Efficiently Modeling Long Sequences with Structured State Spaces2022in the sky ✦