
Causal Discovery in Linear Structural Causal Models with Deterministic Relations
Linear structural causal models (SCMs) – in which each observed variable...
read it

Causal Effect Identification with Contextspecific Independence Relations of Control Variables
We study the problem of causal effect identification from observational ...
read it

Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias
We consider the problem of learning the causal MAG of a system from obse...
read it

Information Theoretic Measures for Fairnessaware Feature Selection
Machine learning algorithms are increasingly used for consequential deci...
read it

The Complexity of NonconvexStronglyConcave Minimax Optimization
This paper studies the complexity for finding approximate stationary poi...
read it

Impact of Data Processing on Fairness in Supervised Learning
We study the impact of pre and post processing for reducing discriminati...
read it

A Recursive Markov BlanketBased Approach to Causal Structure Learning
One of the main approaches for causal structure learning is constraintb...
read it

LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
The causal relationships among a set of random variables are commonly re...
read it

Global Convergence and VarianceReduced Optimization for a Class of NonconvexNonconcave Minimax Problems
Nonconvex minimax problems appear frequently in emerging machine learnin...
read it

Adversarial Policies in Learning Systems with Malicious Experts
We consider a learning system based on the conventional multiplicative w...
read it

ModelAugmented NearestNeighbor Estimation of Conditional Mutual Information for Feature Selection
Markov blanket feature selection, while theoretically optimal, generally...
read it

Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs
The main way for defining equivalence among acyclic directed graphs is b...
read it

Interventional Experiment Design for Causal Structure Learning
It is known that from purely observational data, a causal DAG is identif...
read it

Learning Linear NonGaussian Causal Models in the Presence of Latent Variables
We consider the problem of learning causal models from observational dat...
read it

Database Alignment with Gaussian Features
We consider the problem of aligning a pair of databases with jointly Gau...
read it

Partial Recovery of ErdősRényi Graph Alignment via kCore Alignment
We determine information theoretic conditions under which it is possible...
read it

ScheduLeak: A Novel Scheduler SideChannel Attack Against RealTime Autonomous Control Systems
Realtime autonomous control systems are often the core of safety critic...
read it

REORDER: Securing DynamicPriority RealTime Systems Using Schedule Obfuscation
Modern realtime systems (RTS) are increasingly the focus of security th...
read it

Fundamental Limits of Database Alignment
We consider the problem of aligning a pair of databases with correlated ...
read it

On the Performance of a Canonical Labeling for Matching Correlated ErdősRényi Graphs
Graph matching in two correlated random graphs refers to the task of ide...
read it

Counting and Uniform Sampling from Markov Equivalent DAGs
We propose an exact solution for the problem of finding the size of a Ma...
read it

Nonparametric Hawkes Processes: Online Estimation and Generalization Bounds
In this paper, we design a nonparametric online algorithm for estimating...
read it

Fairness in Supervised Learning: An Information Theoretic Approach
Automated decision making systems are increasingly being used in realwo...
read it

Budgeted Experiment Design for Causal Structure Learning
We study the problem of causal structure learning when the experimenter ...
read it

Learning Causal Structures Using Regression Invariance
We study causal inference in a multienvironment setting, in which the f...
read it

A Reconnaissance Attack Mechanism for FixedPriority RealTime Systems
In realtime embedded systems (RTS), failures due to security breaches c...
read it

A New Measure of Conditional Dependence
Measuring conditional dependencies among the variables of a network is o...
read it

Learning Vector Autoregressive Models with Latent Processes
We study the problem of learning the support of transition matrix betwee...
read it

Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments
We study the problem of causal structure learning over a set of random v...
read it

Interaction Information for Causal Inference: The Case of Directed Triangle
Interaction information is one of the multivariate generalizations of mu...
read it

Learning Network of Multivariate Hawkes Processes: A Time Series Approach
Learning the influence structure of multiple time series data is of grea...
read it

Efficient Neighborhood Selection for Gaussian Graphical Models
This paper addresses the problem of neighborhood selection for Gaussian ...
read it

Directed Information Graphs
We propose a graphical model for representing networks of stochastic pro...
read it
Negar Kiyavash
is this you? claim profile
Associate Professor of Electrical and Computer Engineering at University of Illinois at UrbanaChampaign