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Found 11 papers, 2 papers with code
ColA: Collaborative Adaptation with Gradient Learning
We introduce Collaborative Adaptation (ColA) with Gradient Learning (GL), a parameter-free, model-agnostic fine-tuning approach that decouples the computation of the gradient of hidden representations and parameters.
Vision-language Assisted Attribute Learning
Attribute labeling at large scale is typically incomplete and partial, posing significant challenges to model optimization.
A Framework for Incentivized Collaborative Learning
Collaborations among various entities, such as companies, research labs, AI agents, and edge devices, have become increasingly crucial for achieving machine learning tasks that cannot be accomplished by a single entity alone.
PI-FL: Personalized and Incentivized Federated Learning
Personalized FL has been widely used to cater to heterogeneity challenges with non-IID data.
Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading
We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19, 461 whole-slide images of prostate cancer from multiple centers.
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders
Recommender Systems (RSs) have become increasingly important in many application domains, such as digital marketing.
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
Federated Learning (FL) is a machine learning approach that addresses privacy and data transfer costs by computing data at the source.
Information Laundering for Model Privacy
In this work, we propose information laundering, a novel framework for enhancing model privacy.
Assisted Learning: A Framework for Multi-Organization Learning
In an increasing number of AI scenarios, collaborations among different organizations or agents (e. g., human and robots, mobile units) are often essential to accomplish an organization-specific mission.
Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment
Pedestrians in videos have a wide range of appearances such as body poses, occlusions, and complex backgrounds, and there exists the proposal shift problem in pedestrian detection that causes the loss of body parts such as head and legs.
Ranked #27 on
Pedestrian Detection
on Caltech
Mimicing the Kane-Mele type spin orbit interaction by spin-flexual phonon coupling in graphene devices
On the efforts of enhancing the spin orbit interaction (SOI) of graphene for seeking the dissipationless quantum spin Hall devices, unique Kane-Mele type SOI and high mobility samples are desired.
Mesoscale and Nanoscale Physics
