by instadatahelp | Aug 31, 2023 | AI Blogs
Variational Inverting Network for Statistical Inverse Problems of Partial Differential Equations Authors: Junxiong Jia, Yanni Wu, Peijun Li, Deyu Meng; 24(201):1−60, 2023. Abstract In order to address the uncertainties in inverse problems of partial differential...
![InstaTune: Rapid Neural Architecture Search During Fine-Tuning. (arXiv:2308.15609v1 [cs.LG])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Aug 31, 2023 | AI Blogs
One-Shot Neural Architecture Search (NAS) algorithms often rely on training a super-network that is hardware agnostic for a specific task. These algorithms then extract optimal sub-networks from the trained super-network for different hardware platforms. However,...
by instadatahelp | Aug 31, 2023 | AI Blogs
Label Distribution Changing Learning with Sample Space Expanding Authors: Chao Xu, Hong Tao, Jing Zhang, Dewen Hu, Chenping Hou; 24(36):1−48, 2023. Abstract As data collection methods continue to evolve, label ambiguity has become prevalent in various applications....
by instadatahelp | Aug 31, 2023 | AI Blogs
Training powerful AI systems to perform complex tasks can be challenging when it comes to providing robust training signals that are resistant to manipulation. One specific concern is measurement tampering, where the AI system alters multiple measurements to make it...
by instadatahelp | Aug 31, 2023 | AI Blogs
Multiplayer Performative Prediction: Learning in Decision-Dependent Games Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff; 24(202):1−56, 2023. Abstract This paper introduces a new game theoretic framework called multi-player...
by instadatahelp | Aug 31, 2023 | AI Blogs
The emergence of graph neural networks (GNNs) as a popular area of deep learning has sparked interest in their ability to learn from graph-structured data. However, when dealing with large-scale graphs, the computational and memory requirements of training GNNs can...
