Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), and the Internet. The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The...
1.A method, comprising:obtaining geometric information associated with a physical environment of a communication device participating in a multi-user communication session;determining an activity type for the multi-user communication session;determining a recommended avatar placement based on the geometric in...
A classifier is learned on top of the representations for pneumonia classification. Meanwhile, the representations are further enhanced in a contrastive learning manner, discriminating the positive (orange arrows) and negative (blue arrows) pairs after being mapped by the projection network into the dp...
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1.1 Motivation Machine learning addresses the problem of automatically learning computer pro- grams from data. A typical machine learning system consists of three components [5]: Machine Learning = Representation + Objective + Optimization. (1.1) That is, to build an effective machine learning system...
Recent years have witnessed the emergence of deep learning-based methods as potentially useful tools for predicting molecular properties, primarily due to their remarkable capability of automatically extracting effective features from simple input data. Notably, a diverse range of neural network architectures...
Supervised pre-training then becomes the predominant recipe in visual representation learning, with a scaling-up trend in the size and complex- ity of the network [47] as well as the size of the training dataset, e.g., JFT-300M [88] and Instagram-1B [...
One may also find many approaches from the network science community in the field of community detection [57, 58], and in particular multiscale community detection [59–61]. All these methods are concerned with providing a multiresolution description of the graph structure, but do not consider ...
To further bridge the gap between clip-level and video-level representations, we intuitively introduce a learning objective to model temporal order dependency between local clips and global video. In particular, we have access to the temporal order of the sampled clips in accordance with the croppin...
Object recognition in the natural world usually occurs in the presence of multiple surrounding objects, but responses of neurons in inferotemporal (IT) cortex, the large brain area responsible for object recognition, have mostly been studied only to isolated objects. We study rules governing response...