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Found 4 papers, 1 papers with code
VALID: a Validated Algorithm for Learning in Decentralized Networks with Possible Adversarial Presence
We require (a) convergence to a global empirical loss minimizer when adversaries are absent, and (b) either detection of adversarial presence of convergence to an admissible consensus irrespective of the adversarial configuration.
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning
A key novelty of our work is to develop solution accuracy-independent algorithms that do not require large batch gradients (and function evaluations) for solving federated CO problems.
RELDEC: Reinforcement Learning-Based Decoding of Moderate Length LDPC Codes
In this work we propose RELDEC, a novel approach for sequential decoding of moderate length low-density parity-check (LDPC) codes.
Generative Adversarial User Privacy in Lossy Single-Server Information Retrieval
We propose to extend the concept of private information retrieval by allowing for distortion in the retrieval process and relaxing the perfect privacy requirement at the same time.
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