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Yeah. I mean -- this is Mark Jones. We've talked about a lot that our client retention decline is really largely based on pricing action. And so, you could see in the third quarter, we had less price increase in the book, just the difference between the PIF growth and the premium g...
Yeah, yeah, yeah. So let me answer the question a couple of ways. First of all, a spot observation on non-comp expense in the year. So our non-comp was up 8% ex-litigation. Of about $900 million of non-comp expense increase year-over-year, about two-thirds, in excess of $600 ...
to enable access to capital for more women entrepreneurs.As of March 2023,the facility had reached more than 164,000 women entrepreneurs,eclipsing the 100,000 target set when t 54、he initiative was launched,and contributing to an over$4.5 billion increase in the volume of loans on-lent by ...
Traditional vector attention mechanisms suffer from a rapid increase in the number of parameters in the multi-layer perceptron (MLP) used for weight encoding, as the number of input embedding channels increases. This large parameter scale limits the model’s generalization capabilities, leading to ove...
Adjusting the class weight in the training stage is a critical step in reducing the influence of the imbalance of the data. If the data are imbalanced, the models focus on the class with a larger amount. Models pay less attention to the class with a smaller amount. To reduce the influence...
Microservices can also increase costs of monitoring, debugging, and deployment (and hence cause greater downtime and worse performance). Suboptimality on these dimensions, however, may be optimal. First, rather than scale the entire app, with Microservices we can scale services, saving resources. ...
Microservices can also increase costs of monitoring, debugging, and deployment (and hence cause greater downtime and worse performance). Suboptimality on these dimensions, however, may be optimal. First, rather than scale the entire app, with Microservices we can scale services, saving resources. ...
Adjusting the class weight in the training stage is a critical step in reducing the influence of the imbalance of the data. If the data are imbalanced, the models focus on the class with a larger amount. Models pay less attention to the class with a smaller amount. To reduce the influence...
With the increase of the embedding dimension, the training time also increases, so we choose the embedding size of 64. Figure 3. Influence of the embedding dimension. Influence of the number of GCN layers: To research whether the number of GCN layers is helpful for our model, we change ...