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Found 5 papers, 2 papers with code
Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction
In the context of Exploitation-and-Exploration for CTR prediction, recent studies have attempted to utilize the prediction uncertainty along with model prediction as the reward score.
Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling
To strike a balance in this trade-off, we propose Elapsed-Time Sampling Delayed Feedback Model (ES-DFM), which models the relationship between the observed conversion distribution and the true conversion distribution.
RRF102: Meeting the TREC-COVID Challenge with a 100+ Runs Ensemble
In this paper, we report the results of our participation in the TREC-COVID challenge.
Learning-to-Rank with BERT in TF-Ranking
This paper describes a machine learning algorithm for document (re)ranking, in which queries and documents are firstly encoded using BERT [1], and on top of that a learning-to-rank (LTR) model constructed with TF-Ranking (TFR) [2] is applied to further optimize the ranking performance.
Deep Keyphrase Generation
Keyphrase provides highly-condensed information that can be effectively used for understanding, organizing and retrieving text content.
