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Found 6 papers, 2 papers with code
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits
This paper considers the problem of annotating datapoints using an expert with only a few annotation rounds in a label-scarce setting.
CAFIN: Centrality Aware Fairness inducing IN-processing for Unsupervised Representation Learning on Graphs
Unsupervised Representation Learning on graphs is gaining traction due to the increasing abundance of unlabelled network data and the compactness, richness, and usefulness of the representations generated.
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
We follow a principled approach to address the above FRCS problems and develop a new federated learning method using the Shapley value concept from cooperative game theory.
Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks
To the best of our knowledge, this is the first direct unsupervised approach for edge embedding in homogeneous information networks, without relying on the node embeddings.
Cogniculture: Towards a Better Human-Machine Co-evolution
Research in Artificial Intelligence is breaking technology barriers every day.
All Fingers are not Equal: Intensity of References in Scientific Articles
Research accomplishment is usually measured by considering all citations with equal importance, thus ignoring the wide variety of purposes an article is being cited for.
