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Found 8 papers, 1 papers with code
SplitGP: Achieving Both Generalization and Personalization in Federated Learning
A fundamental challenge to providing edge-AI services is the need for a machine learning (ML) model that achieves personalization (i. e., to individual clients) and generalization (i. e., to unseen data) properties concurrently.
Few-Round Learning for Federated Learning
Of central issues that may limit a widespread adoption of FL is the significant communication resources required in the exchange of updated model parameters between the server and individual clients over many communication rounds.
TiVGAN: Text to Image to Video Generation with Step-by-Step Evolutionary Generator
Advances in technology have led to the development of methods that can create desired visual multimedia.
Sequencing seismograms: A panoptic view of scattering in the core-mantle boundary region
In nearly half of the diffracting waveforms, we detected seismic waves scattered by three-dimensional structures near the core-mantle boundary.
Crowdsourced Labeling for Worker-Task Specialization Model
We consider crowdsourced labeling under a $d$-type worker-task specialization model, where each worker and task is associated with one particular type among a finite set of types and a worker provides a more reliable answer to tasks of the matched type than to tasks of unmatched types.
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
The base and novel classifiers quickly adapt to a given task by utilizing the TAR.
Parity Queries for Binary Classification
We define the query difficulty $\bar{d}$ as the average size of the query subsets and the sample complexity $n$ as the minimum number of measurements required to attain a given recovery accuracy.
Generating a Fusion Image: One's Identity and Another's Shape
Generating a novel image by manipulating two input images is an interesting research problem in the study of generative adversarial networks (GANs).
