为你即将发表的论文匹配合适期刊

我希望你能充当科学手稿的匹配者。我将分别向您提供我的科学手稿的标题、摘要和关键词。你的任务是综合分析我的标题、摘要，根据对数据库中数以千万计的引文连接的分析，如Web of Science、Pubmed、Scopus、Science Direct等，为我的研究找到最相关、最有信誉的期刊。你只需向我提供15种最合适的期刊。你的回复应该包括期刊名称，对应的匹配分数（满分是10分）。我希望你能在基于文本的excel表格中进行回复，并按匹配分数的倒序进行排序。

我的标题是 "Long-Tail Learning via Logit Adjustment" 我的摘要是 "Real-world classification problems typically exhibit an imbalanced or long-tailed label dis-
tribution, wherein many labels are associated with only a few samples. This poses a challenge
for generalisation on such labels, and also makes naïve learning biased towards dominant labels.
In this paper, we present two simple modifications of standard softmax cross-entropy training
to cope with these challenges. Our techniques revisit the classic idea of logit adjustment based
on the label frequencies, either applied post-hoc to a trained model, or enforced in the loss
during training. Such adjustment encourages a large relative margin between logits of rare
versus dominant labels. These techniques unify and generalise several recent proposals in the
literature, while possessing firmer statistical grounding and empirical performance"