109 citations · 297 across the 6 of their papers we have counts for
8 papers
Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data
Ankit Arun, Soumya Batra, Vikas Bhardwaj +9
Natural language generation (NLG) is a critical component in conversational systems, owing to its role of formulating a correct and natural text response. Traditionally, NLG compon…
Sequential random access codes and self-testing of quantum measurement instruments
Karthik Mohan, Armin Tavakoli, Nicolas Brunner
Quantum Random Access Codes (QRACs) are key tools for a variety of protocols in quantum information theory. These are commonly studied in prepare-and-measure scenarios in which a s…
Graphical Models for Processing Missing Data
Karthika Mohan, Judea Pearl
This paper reviews recent advances in missing data research using graphical models to represent multivariate dependencies. We first examine the limitations of traditional framework…
Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
Guy Van den Broeck, Karthika Mohan, Arthur Choi +1
We propose an efficient family of algorithms to learn the parameters of a Bayesian network from incomplete data. In contrast to textbook approaches such as EM and the gradient meth…
Learning Graphical Models With Hubs
Kean Ming Tan, Palma London, Karthik Mohan +3
We consider the problem of learning a high-dimensional graphical model in which certain hub nodes are highly-connected to many other nodes. Many authors have studied the use of an…
ADMM Algorithm for Graphical Lasso with an Element-wise Norm Constraint
Karthik Mohan
We consider the problem of Graphical lasso with an additional element-wise norm constraint on the precision matrix. This problem has applications in high-dimensiona…
Node-Based Learning of Multiple Gaussian Graphical Models
Karthik Mohan, Palma London, Maryam Fazel +2
We consider the problem of estimating high-dimensional Gaussian graphical models corresponding to a single set of variables under several distinct conditions. This problem is motiv…
A Simplified Approach to Recovery Conditions for Low Rank Matrices
Samet Oymak, Karthik Mohan, Maryam Fazel +1
Recovering sparse vectors and low-rank matrices from noisy linear measurements has been the focus of much recent research. Various reconstruction algorithms have been studied, incl…