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20142022
most citedThroughput-Optimal Topology Design for Cross-Silo Federated Learning

50 citations

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5 papers · 1 filter

cs.LG2021

Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods

Peru Bhardwaj, John Kelleher, Luca Costabello +1

Despite the widespread use of Knowledge Graph Embeddings (KGE), little is known about the security vulnerabilities that might disrupt their intended behaviour. We study data poison…

cs.LG20218 cited

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties

Lisa Schut, Oscar Key, Rory McGrath +4

Counterfactual explanations (CEs) are a practical tool for demonstrating why machine learning classifiers make particular decisions. For CEs to be useful, it is important that they…

cs.LG2020

End-To-End Dilated Variational Autoencoder with Bottleneck Discriminative Loss for Sound Morphing -- A Preliminary Study

Matteo Lionello, Hendrik Purwins

We present a preliminary study on an end-to-end variational autoencoder (VAE) for sound morphing. Two VAE variants are compared: VAE with dilation layers (DC-VAE) and VAE only with…

cs.LG202050 cited

Throughput-Optimal Topology Design for Cross-Silo Federated Learning

Othmane Marfoq, Chuan Xu, Giovanni Neglia +1

Federated learning usually employs a client-server architecture where an orchestrator iteratively aggregates model updates from remote clients and pushes them back a refined model.…

cs.LG20205 cited

ChemoVerse: Manifold traversal of latent spaces for novel molecule discovery

Harshdeep Singh, Nicholas McCarthy, Qurrat Ul Ain +1

In order to design a more potent and effective chemical entity, it is essential to identify molecular structures with the desired chemical properties. Recent advances in generative…