4 citations · 8 across the 14 of their papers we have counts for
18 papers
A Joint Power-Privacy Control Framework for Decentralized Learning over Heterogeneous Wireless Multicasting Networks
Amir Ziaeddini, Yauhen Yakimenka, Joerg Kliewer
In this paper, we propose a decentralized learning framework that incorporates both power control and privacy guarantees. Specifically, we enable a set of clients in a wireless mul…
Context-Aware Search and Retrieval Under Token Erasure
Sara Ghasvarianjahromi, Joshua Barr, Yauhen Yakimenka +1
This paper introduces and analyzes a search and retrieval model for RAG-like systems under {token} erasures. We provide an information-theoretic analysis of remote document retriev…
Communication-Constrained Private Decentralized Online Personalized Mean Estimation
Yauhen Yakimenka, Hsuan-Yin Lin, Eirik Rosnes +1
We consider the problem of communication-constrained collaborative personalized mean estimation under a privacy constraint in an environment of several agents continuously receivin…
Differentially-Private Decentralized Learning in Heterogeneous Multicast Networks
Amir Ziaeddini, Yauhen Yakimenka, Jörg Kliewer
We propose a power-controlled differentially private decentralized learning algorithm designed for a set of clients aiming to collaboratively train a common learning model. The net…
Minimax Data Sanitization with Distortion Constraint and Adversarial Inference
Amirarsalan Moatazedian, Yauhen Yakimenka, Rémi A. Chou +1
We study a privacy-preserving data-sharing setting where a privatizer transforms private data into a sanitized version observed by an authorized reconstructor and two unauthorized…
Context-Aware Search and Retrieval Over Erasure Channels
Sara Ghasvarianjahromi, Yauhen Yakimenka, Jörg Kliewer
This paper introduces and analyzes a search and retrieval model that adopts key semantic communication principles from retrieval-augmented generation. We specifically present an in…
Differentially-Private Collaborative Online Personalized Mean Estimation
Yauhen Yakimenka, Chung-Wei Weng, Hsuan-Yin Lin +2
We consider the problem of collaborative personalized mean estimation under a privacy constraint in an environment of several agents continuously receiving data according to arbitr…
VALID: a Validated Algorithm for Learning in Decentralized Networks with Possible Adversarial Presence
Mayank Bakshi, Sara Ghasvarianjahromi, Yauhen Yakimenka +3
We introduce the paradigm of validated decentralized learning for undirected networks with heterogeneous data and possible adversarial infiltration. We require (a) convergence to a…
Straggler-Resilient Differentially-Private Decentralized Learning
Yauhen Yakimenka, Chung-Wei Weng, Hsuan-Yin Lin +2
We consider the straggler problem in decentralized learning over a logical ring while preserving user data privacy. Especially, we extend the recently proposed framework of differe…
Optimal Rate-Distortion-Leakage Tradeoff for Single-Server Information Retrieval
Yauhen Yakimenka, Hsuan-Yin Lin, Eirik Rosnes +1
Private information retrieval protocols guarantee that a user can privately and losslessly retrieve a single file from a database stored across multiple servers. In this work, we p…
Generative Adversarial User Privacy in Lossy Single-Server Information Retrieval
Chung-Wei Weng, Yauhen Yakimenka, Hsuan-Yin Lin +2
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.…
On the Capacity of Private Monomial Computation
Yauhen Yakimenka, Hsuan-Yin Lin, Eirik Rosnes
In this work, we consider private monomial computation (PMC) for replicated noncolluding databases. In PMC, a user wishes to privately retrieve an arbitrary multivariate monomial f…
Failure Analysis of the Interval-Passing Algorithm for Compressed Sensing
Yauhen Yakimenka, Eirik Rosnes
In this work, we perform a complete failure analysis of the interval-passing algorithm (IPA) for compressed sensing, an efficient iterative algorithm for reconstructing a -spars…
Stopping Redundancy Hierarchy Beyond the Minimum Distance
Yauhen Yakimenka, Vitaly Skachek, Irina E. Bocharova +1
Stopping sets play a crucial role in failure events of iterative decoders over a binary erasure channel (BEC). The -th stopping redundancy is the minimum number of rows in th…
Distance Properties of Short LDPC Codes and their Impact on the BP, ML and Near-ML Decoding Performance
Irina E. Bocharova, Boris D. Kudryashov, Vitaly Skachek +1
Parameters of LDPC codes, such as minimum distance, stopping distance, stopping redundancy, girth of the Tanner graph, and their influence on the frame error rate performance of th…
BP-LED decoding algorithm for LDPC codes over AWGN channels
Irina E. Bocharova, Boris D. Kudryashov, Vitaly Skachek +1
A new method for low-complexity near-maximum-likelihood (ML) decoding of low-density parity-check (LDPC) codes over the additive white Gaussian noise channel is presented. The prop…
On Failing Sets of the Interval-Passing Algorithm for Compressed Sensing
Yauhen Yakimenka, Eirik Rosnes
In this work, we analyze the failing sets of the interval-passing algorithm (IPA) for compressed sensing. The IPA is an efficient iterative algorithm for reconstructing a k-sparse…
Refined Upper Bounds on Stopping Redundancy of Binary Linear Codes
Yauhen Yakimenka, Vitaly Skachek
The -th stopping redundancy of the binary code , , is defined as the minimum number of rows in the parity-check matrix o…