activity
20112019
most citedInformation-Theoretic Viewpoints on Optimal Causal Coding-Decoding Problems

19 citations · 59 across the 11 of their papers we have counts for

collaborators

14 papers

cs.IT2019★ 9 cited

Direct and Indirect Effects -- An Information Theoretic Perspective

Gabriel Schamberg, William Chapman, Shang-Ping Xie +1

Information theoretic (IT) approaches to quantifying causal influences have experienced some popularity in the literature, in both theoretical and applied (e.g. neuroscience and cl…

cs.IT2019

On the Bias of Directed Information Estimators

Gabriel Schamberg, Todd P. Coleman

When estimating the directed information between two jointly stationary Markov processes, it is typically assumed that the recipient of the directed information is itself Markov of…

cs.IT2019★ 1 cited

Construction and Analysis of Posterior Matching in Arbitrary Dimensions via Optimal Transport

Diego A. Mesa, Rui Ma, Siva K. Gorantla +1

The posterior matching scheme, for feedback encoding of a message point lying on the unit interval over memoryless channels, maximizes mutual information for an arbitrary number of…

cs.IT2018

Measuring Sample Path Causal Influences with Relative Entropy

Gabriel Schamberg, Todd P. Coleman

We present a sample path dependent measure of causal influence between time series. The proposed causal measure is a random sequence, a realization of which enables identification…

cs.IT2018★ 1 cited

A Sample Path Measure of Causal Influence

Gabriel Schamberg, Todd P. Coleman

We present a sample path dependent measure of causal influence between two time series. The proposed measure is a random variable whose expected sum is the directed information. A…

stat.CO2018★ 2 cited

Bayesian Lasso Posterior Sampling via Parallelized Measure Transport

Marcela Mendoza, Alexis Allegra, Todd P. Coleman

It is well known that the Lasso can be interpreted as a Bayesian posterior mode estimate with a Laplacian prior. Obtaining samples from the full posterior distribution, the Bayesia…

math.OC2017★ 12 cited

A Modularized Efficient Framework for Non-Markov Time Series Estimation

Gabriel Schamberg, Demba Ba, Todd P. Coleman

We present a compartmentalized approach to finding the maximum a-posteriori (MAP) estimate of a latent time series that obeys a dynamic stochastic model and is observed through noi…

cs.IT2016

Timing Channel: Achievable Rate in the Finite Block-Length Regime

Thomas J. Riedl, Todd P. Coleman, Andrew C. Singer

The exponential server timing channel is known to be the simplest, and in some sense canonical, queuing timing channel. The capacity of this infinite-memory channel is known. Here,…

stat.ML2015★ 4 cited

Tractable Fully Bayesian Inference via Convex Optimization and Optimal Transport Theory

Sanggyun Kim, Diego Mesa, Rui Ma +1

We consider the problem of transforming samples from one continuous source distribution into samples from another target distribution. We demonstrate with optimal transport theory…

math.OC2013

An Optimizer's Approach to Stochastic Control Problems with Nonclassical Information Structures

Ankur A. Kulkarni, Todd P. Coleman

We present an optimization-based approach to stochastic control problems with nonclassical information structures. We cast these problems equivalently as optimization prob- lems on…

cs.IT2012

Directed Information Graphs

Christopher J. Quinn, Negar Kiyavash, Todd P. Coleman

We propose a graphical model for representing networks of stochastic processes, the minimal generative model graph. It is based on reduced factorizations of the joint distribution…

cs.IT2011★ 19 cited

Information-Theoretic Viewpoints on Optimal Causal Coding-Decoding Problems

Siva Gorantla, Todd Coleman

In this paper we consider an interacting two-agent sequential decision-making problem consisting of a Markov source process, a causal encoder with feedback, and a causal decoder. M…

cs.IT2011★ 6 cited

Causal Dependence Tree Approximations of Joint Distributions for Multiple Random Processes

Christopher J. Quinn, Todd P. Coleman, Negar Kiyavash

We investigate approximating joint distributions of random processes with causal dependence tree distributions. Such distributions are particularly useful in providing parsimonious…

cs.IT2011★ 5 cited

Bit-wise Unequal Error Protection for Variable Length Block Codes with Feedback

Baris Nakiboglu, Siva K. Gorantla, Lizhong Zheng +1

The bit-wise unequal error protection problem, for the case when the number of groups of bits is fixed, is considered for variable length block codes with feedback. An encod…