7 citations · 8 across the 8 of their papers we have counts for
9 papers
Adaptive Agent Design
Raj Kiriti Velicheti, Subhonmesh Bose, Tamer Başar
We consider an agent acting against a general non-Markovian environment. The agent maintains its agent states, but is free to choose a transition kernel across those states and opt…
Harnessing Information in Incentive Design
Raj Kiriti Velicheti, Subhonmesh Bose, Tamer Başar
Incentive design deals with interaction between a principal and an agent where the former can shape the latter's utility through a policy commitment. It is well known that the prin…
A Soft Inducement Framework for Incentive-Aided Steering of No-Regret Players
Asrin Efe Yorulmaz, Raj Kiriti Velicheti, Melih Bastopcu +1
In this work, we investigate a steering problem in a mediator-augmented two-player normal-form game, where the mediator aims to guide players toward a specific action profile throu…
Remote Estimation Games with Random Walk Processes: Stackelberg Equilibrium
Atahan Dokme, Raj Kiriti Velicheti, Melih Bastopcu +1
Remote estimation is a crucial element of real time monitoring of a stochastic process. While most of the existing works have concentrated on obtaining optimal sampling strategies,…
Learning How to Strategically Disclose Information
Raj Kiriti Velicheti, Melih Bastopcu, S. Rasoul Etesami +1
Strategic information disclosure, in its simplest form, considers a game between an information provider (sender) who has access to some private information that an information rec…
Value of Information in Games with Multiple Strategic Information Providers
Raj Kiriti Velicheti, Melih Bastopcu, Tamer Başar
In the classical communication setting multiple senders having access to the same source of information and transmitting it over channel(s) to a receiver in general leads to a decr…
Secure Byzantine-Robust Distributed Learning via Clustering
Raj Kiriti Velicheti, Derek Xia, Oluwasanmi Koyejo
Federated learning systems that jointly preserve Byzantine robustness and privacy have remained an open problem. Robust aggregation, the standard defense for Byzantine attacks, gen…
Design of Experiments with Imputable Feature Data: An Entropy-Based Approach
Raj K. Velicheti, Amber Srivastava, Srinivasa M. Salapaka
Tactical selection of experiments to estimate an underlying model is an innate task across various fields. Since each experiment has costs associated with it, selecting statistical…
On Determining and Qualifying the Number of Superstates in Aggregation of Markov Chains
Amber Srivastava, Raj K. Velicheti, Srinivasa M. Salapaka
Many studies involving large Markov chains require determining a smaller representative (aggregated) chains. Each {\em superstate} in the representative chain represents a {\em gro…