In the classical lossy source coding problem, one encodes long blocks of source symbols
that enables the distortion to approach the ultimate Shannon limit. Such a block-coding …

In nonstationary bandit learning problems, the decision-maker must continually gather
information and adapt their action selection as the latent state of the environment evolves. In …

The remote wireless control of industrial systems is one of the major use cases for 5G and
beyond systems: in these cases, the massive amounts of sensory information that need to be …

We revisit the sequential rate-distortion (SRD) tradeoff problem for vector-valued Gauss-
Markov sources with mean-squared error distortion constraints. Our study is partly motivated …

We study the problem of characterizing and computing the Gaussian nonanticipative rate-
distortion function (NRDF) of partially observable multivariate Gauss–Markov processes with …

In this article, we revisit the sequential source-coding framework to analyze fundamental
performance limitations of discrete-time stochastic control systems subject to feedback data …

Optimal zero-delay coding (quantization) of-valued linearly generated Markov sources is
studied under quadratic distortion. The structure and existence of deterministic and …

Motivated by control with communication constraints, in this work we develop a time-
invariant data compression architecture for linear-quadratic-Gaussian (LQG) control with …

The existence of an optimal reverse-waterfilling algorithm to compute the nonanticipative
rate distortion function (NRDF) for time-invariant vector-valued Gauss–Markov processes …

We consider the framework of transfer-entropy-regularized Markov decision process
(TERMDP) in which the weighted sum of the classical state-dependent cost and the transfer …