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CNN CNN Newsroom With Jim Acosta June 4, 2024 21:10:00

Thank you. you bet. there was a conversation today, so let s go to the white house, and cnn s arlette saenz, what are you learning? president biden is spending the weekend at his home, where he spoke with the german chancellor over the phone. the two men talked about it as well, as recent developments, according to the white house, but that call comes as the president s recent comments about the prospects of nuclear arm embedding remain in the spotlight form john kirby this morning said there s no imminent threat right now of russia uses nuclear weapons, but the president s comments simply speak to the gravity with which ....

White House , Let S Go , You Bet , Joe Biden , Arlette Saenz , John Kirby ,

Scientists monitor vitals by embedding sensors into t-shirts

New low-cost sensors in t-shirts and face masks that track breathing, heart rate, and ammonia have been embedded by imperial researchers. ....

Fahad Alshabouna , T Shirts , Ews India ,

Consultancy service for environmental compliance

Environmental Monitoring Solutions (EMS) provides consultancy services and monitoring solutions to help clients meet and maintain environmental compliance, improve efficiency and manage environmental impact. Click to read more. ....

Environmental Monitoring Solutions , Smart Wastewater ,

"Object-aware Policy Network in Deep Recommender Systems" by Guoqiang Zhou, Zhangxian Xu et al.

Deep learning has been successfully applied in the recommender system. Low-dimensional dense embedding is typically used to represent the feature of users and items. To optimize the model, some models propose to dynamically search the embedding size based on the popularity of different users and items. However, these models ignore the interaction between the user and the item which will hinder the optimization of the features in embedding. In this paper, we propose Object-aware Policy Network (OPN) and introduces an object-aware method that is used for optimizing the features in embedding. We evaluate our model on the two real-world benchmark datasets. With less than 10% increased time consumption in all experiments, the results show that our proposed model is able to improve the performance of binary classification task by a margin of 0.30 and multiclass classification task by a margin of 0.35 compared to the best accuracies achieced by baselines on different datasests. ....

Object Aware Policy Network , Deep Learning , Eature Optimizing , Object Aware , Recommender System ,