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Found 10 papers, 8 papers with code
Attacking Byzantine Robust Aggregation in High Dimensions
Designing such aggregators is challenging when dealing with high dimensions.
Scalable Neural Network Training over Distributed Graphs
We present RETEXO, the first framework which eliminates the severe communication bottleneck in distributed GNN training while respecting any given data partitioning configuration.
Membership Inference Attacks and Generalization: A Causal Perspective
Our causal models also show a new connection between generalization and MI attacks via their shared causal factors.
LPGNet: Link Private Graph Networks for Node Classification
In this paper, we present a new neural network architecture called LPGNet for training on graphs with privacy-sensitive edges.
EPIE Dataset: A Corpus For Possible Idiomatic Expressions
Idiomatic expressions have always been a bottleneck for language comprehension and natural language understanding, specifically for tasks like Machine Translation(MT).
Scalable Quantitative Verification For Deep Neural Networks
But these existing techniques provide either scalability to large networks or formal guarantees, not both.
Quantitative Verification of Neural Networks And its Security Applications
Neural networks are increasingly employed in safety-critical domains.
Practical Verifiable In-network Filtering for DDoS defense
In this paper, we show the technical feasibility of verifiable in-network filtering, called VIF, that offers filtering verifiability to DDoS victims and neighbor ASes.
Cryptography and Security
OHIE: Blockchain Scaling Made Simple
Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth.
Distributed, Parallel, and Cluster Computing
Finding The Greedy, Prodigal, and Suicidal Contracts at Scale
On a subset of3, 759 contracts which we sampled for concrete validation and manual analysis, we reproduce real exploits at a true positive rate of 89%, yielding exploits for3, 686 contracts.
Cryptography and Security
