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Found 15 papers, 2 papers with code
Self-Duplicating Random Walks for Resilient Decentralized Learning on Graphs
We propose a decentralized algorithm called DECAFORK that can maintain the number of RWs in the graph around a desired value even in the presence of arbitrary RW failures.
Scalable and Reliable Over-the-Air Federated Edge Learning
However, FEEL still suffers from a communication bottleneck due to the transmission of high-dimensional model updates from the clients to the federator.
Maximal-Capacity Discrete Memoryless Channel Identification
Based on this capacity estimator, a gap-elimination algorithm termed BestChanID is proposed, which is oblivious to the capacity-achieving input distribution and is guaranteed to output the DMC with the largest capacity, with a desired confidence.
Private Aggregation in Hierarchical Wireless Federated Learning with Partial and Full Collusion
Existing literature focuses on private aggregation schemes that tackle the privacy problem in federated learning in settings where all users are connected to each other and to the federator.
FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation
Specifically, the server learns the aggregated model of the clients in each group - vanilla federated learning and secure aggregation correspond to the extreme cases of FedGT with group size equal to one and the total number of clients, respectively.
Nested Gradient Codes for Straggler Mitigation in Distributed Machine Learning
Since the number of stragglers in practice is random and unknown a priori, tolerating a fixed number of stragglers can yield a sub-optimal computation load and can result in higher latency.
Secure Over-the-Air Computation using Zero-Forced Artificial Noise
Over-the-air computation has the potential to increase the communication-efficiency of data-dependent distributed wireless systems, but is vulnerable to eavesdropping.
Cost-Efficient Distributed Learning via Combinatorial Multi-Armed Bandits
We consider the distributed SGD problem, where a main node distributes gradient calculations among $n$ workers.
Multiple Criss-Cross Insertion and Deletion Correcting Codes
We show an equivalence between correcting $t$-criss-cross deletions and $t$-criss-cross insertions and show that a code correcting $t$-criss-cross insertions/deletions has redundancy at least $tn + t \log n - \log(t!)$.
Information Theory Information Theory
Decoding of Space-Symmetric Rank Errors
This paper investigates the decoding of certain Gabidulin codes that were transmitted over a channel with space-symmetric errors.
Information Theory Information Theory
Efficient Decoding of Gabidulin Codes over Galois Rings
The new method consists of two steps: (1) solving a syndrome-based key equation to obtain the annihilator polynomial of the error and therefore the column space of the error, (2) solving a key equation based on the received word in order to reconstruct the error vector.
Information Theory Information Theory
Adaptive Private Distributed Matrix Multiplication
A master server owns two private matrices $\mathbf{A}$ and $\mathbf{B}$ and hires worker nodes to help computing their multiplication.
Information Theory Information Theory
On the Gap between Scalar and Vector Solutions of Generalized Combination Networks
We derive new upper and lower bounds on the maximum number of nodes in the middle layer, depending on the network parameters and the alphabet size.
Information Theory Networking and Internet Architecture Social and Information Networks Combinatorics Information Theory
Clustering-Correcting Codes
This family of codes is motivated by the special structure of data that is stored in DNA-based storage systems.
Information Theory Information Theory
Codes Correcting a Burst of Deletions or Insertions
In this paper we close on this gap and provide codes with redundancy at most $\log(n) + (b-1)\log(\log(n)) +b -\log(b)$.
Information Theory Information Theory
