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Found 5 papers, 2 papers with code
P^3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning
In this paper, we identify and study the two mismatches between pre-training and ranking fine-tuning: the training schema gap regarding the differences in training objectives and model architectures, and the task knowledge gap considering the discrepancy between the knowledge needed in ranking and that learned during pre-training.
Collecting and Analyzing Multidimensional Data with Local Differential Privacy
Motivated by this, we first propose novel LDP mechanisms for collecting a numeric attribute, whose accuracy is at least no worse (and usually better) than existing solutions in terms of worst-case noise variance.
Y Chromosome of Aisin Gioro, the Imperial House of Qing Dynasty
We therefore conclude that this haplotype is the Y chromosome of the House of Aisin Gioro.
Populations and Evolution
When coding meets ranking: A joint framework based on local learning
In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm.
