An introduction is given to the use of prototype-based models in supervised machine learning. The main concept of the framework is to represent previously observed data in terms of so-called prototypes, which reflect typical properties of the data. Together with a suitable, discriminative distance ...
Despite the often critical role of machine learning systems in these production environments, computer functionality for decoding or interpreting how these systems make a decision are either absent or lack effectiveness. For example, although some conventional machine learning models, such as neural ...
Finally, we conduct extensive experiments in PTaRL coupled with state-of-the-art deep tabular ML models on various tabular benchmarks and the results have shown our consistent superiority. (在新选项卡中打开) Publication 活动 Microsoft at ICLR 2024 研究院 Microsoft...
Federated learning allows multiple participants to collaborate on training models while preserving privacy. However, traditional federated learning methods do not support continuous learning and are not well-suited for dynamic scenarios. Recently, federated continual learning has emerged as a promising approac...
1. Introduction With the availability of large-scale datasets and the rapid development of deep convolutional architectures, super- vised learning exceeds in computer vision, voice, and ma- chine translation [23]. However, lack of data makes the ex- is...
of experiments using Amazon Mechanical Turk. They not only show the capability of our framework in assessing the interpretability of various part-prototype-based models, but they also are, to the best of our knowledge, the most comprehensive work on evaluating such methods in a unified framework...
(299\times 299\)region from images or their horizontal flips. And we report the results on the backbone of the Inception-Resnet-v2 network25. We initialize network weights with pre-trained models from ImageNet22. The network weights are trained using the mini-batch stochastic gradient descent ...
Although only objects representing the animated models are available, it cannot be considered as an aid to learn prototype-based object-oriented programming, since no detail of the underlying object model is offered. BlueJ [14] is a visual programming environment aimed at education. It supports ...
Zhand and Luo (2019) recommended that marketers run hyper-personalization experiments and then apply the deep learning models to distinguish target customers from the remaining customers with the highest predicted purchase probabilities. Most retailers have embraced the application of AI to marketing ...
Hard classes can be defined as groups of examples that share common traits but are inherently complex or ambiguous to classify, often posing substantial challenges to the accuracy and efficiency of machine learning models. Hard Negtive Mining. The Hard Negative Mining schemes construct mini-batches fo...