Reinforcement learningis a elegant alternative in the absence of groundtruth solutions, as is often the case for understudied problems. As routing problems generally require sequential decision making tominimize a problem-specific cost functions(e.g. the tour length for TSP), they can elegantly be ...
In our research programme, we seek to integrate the three abilities within neural computation, offering a unified framework for learning and reasoning that exploits the parallelism and robustness of connectionism. A neural network can be the machine for computation, inductive learning, and effective ...
Transformer-based deep learning models, as introduced by Vaswani et al. [57] and shown in Fig.7, use self-attention to capture dependencies among all elements in a sequence concurrently. These models calculate the significance weights for each element through the attention mechanism, allowing for ...
For instance, adaptive gesture control systems can provide the system with a means of learning the gesture habits of a given surgeon and automatically adjusting the recognition algorithm in a personalized manner. The further maturation of augmented reality technologies and the resultant use of gestures...
DeepMedic54, known for its robustness in managing noise and artifacts, stands as a strong competitor to the 3D U-Net, trained on glioma images. The V-Net, a nascent innovation designed to accurately segment volumetric medical images, establishes its prowess in segmenting both 2D and 3D MRI ...
adaptor [44]. Thus, MARS-seq2.0 has a comprehensive improvement including throughput, robustness, noise reduction, and cost reduction. Optimization of the conditions indicated above resulted in a sixfold reduction in the cost of library production (from $0.65 to $0.10 per cell) and reduced the ...
一种探究私人化和非独立同分布数据的方法是通过元学习(meta-learning),元学习已经成为模型适应(model adaptation)的流行设置。元学习目标不是直接从数据中学习特定任务的解决方案,而是使机器学习模型能够更好地学习和适应各种不同任务。换句话说,元学习关注的是"学习如何学习"。 3.3.4 何时一个全局联邦训练模型更好 ...
Junker and colleagues [27] devised RNA tomography (tomo-seq), a technique that involves cryosectioning, reverse transcription, and amplification. Notably, this approach eliminates the need for carrier RNA and provides high sensitivity and spatial resolution. The robustness of the tomo-seq protocol was...
Deep clustering for unsupervised learning of visual features. In Proc. European Conference on Computer Vision (ECCV) 132–149 (2018). Deng, Z., Zhang, L., Ghorbani, A. & Zou, J. Improving adversarial robustness via unlabeled out-of-domain. Data. Proc. Mach. Learn. Res. 130, 2845–...
Boyle KJ, Kaul S, Parmeter CF (2015) Meta-analysis: econometric advances and new perspectives towards data synthesis and robustness, chapter 17. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and ...