78 citations · 304 across the 58 of their papers we have counts for
8 papers · 1 filter
Quantizing data for distributed learning
Osama A. Hanna, Yahya H. Ezzeldin, Christina Fragouli +1
We consider machine learning applications that train a model by leveraging data distributed over a trusted network, where communication constraints can create a performance bottlen…
Group testing for overlapping communities
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo +2
In this paper, we propose algorithms that leverage a known community structure to make group testing more efficient. We consider a population organized in connected communities: ea…
Community aware group testing
Pavlos Nikolopoulos, Tao Guo, Sundara Rajan Srinivasavaradhan +2
In this paper, we propose algorithms that leverage a known community structure to make group testing more efficient. We consider a population organized in disjoint communities: eac…
Distortion based Light-weight Security for Cyber-Physical Systems
Gaurav Kumar Agarwal, Mohammed Karmoose, Suhas Diggavi +2
In Cyber-Physical Systems (CPS), inference based on communicated data is of critical significance as it can be used to manipulate or damage the control operations by adversaries. T…
Algorithms for reconstruction over single and multiple deletion channels
Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas Diggavi +1
Recent advances in DNA sequencing technology and DNA storage systems have rekindled the interest in deletion channels. Multiple recent works have looked at variants of sequence rec…
Successive Refinement of Privacy
Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri +2
This work examines a novel question: how much randomness is needed to achieve local differential privacy (LDP)? A motivating scenario is providing {\em multiple levels of privacy}…
Federated Recommendation System via Differential Privacy
Tan Li, Linqi Song, Christina Fragouli
In this paper, we are interested in what we term the federated private bandits framework, that combines differential privacy with multi-agent bandit learning. We explore how differ…
Gaussian 1-2-1 Networks with Imperfect Beamforming
Yahya H. Ezzeldin, Martina Cardone, Christina Fragouli +1
In this work, we study bounds on the capacity of full-duplex Gaussian 1-2-1 networks with imperfect beamforming. In particular, different from the ideal 1-2-1 network model introdu…