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- research-articleAugust 2023
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningPages 3249–3261https://doi.org/10.1145/3580305.3599345Recently, personalized federated learning (pFL) has attracted increasing attention in privacy protection, collaborative learning, and tackling statistical heterogeneity among clients, e.g., hospitals, mobile smartphones, etc. Most existing pFL methods ...
- research-articleSeptember 2021
QuickLoc: Adaptive Deep-Learning for Fast Indoor Localization with Mobile Devices
ACM Transactions on Cyber-Physical Systems (TCPS), Volume 5, Issue 4Article No.: 44, Pages 1–30https://doi.org/10.1145/3461342Indoor localization services are a crucial aspect for the realization of smart cyber-physical systems within cities of the future. Such services are poised to reinvent the process of navigation and tracking of people and assets in a variety of indoor and ...
- research-articleAugust 2021
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
KDD '21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data MiningPages 1017–1026https://doi.org/10.1145/3447548.3467358Successful quantitative investment usually relies on precise predictions of the future movement of the stock price. Recently, machine learning based solutions have shown their capacity to give more accurate stock prediction and become indispensable ...
- tutorialAugust 2014
Scaling up deep learning
KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data miningPage 1966https://doi.org/10.1145/2623330.2630802Deep learning has rapidly moved from a marginal approach in the machine learning community less than ten years ago to one that has strong industrial impact, in particular for high-dimensional perceptual data such as speech and images, but also natural ...
