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09/05/2023
s-ID: Causal Effect Identification in a Sub-Population
Causal inference in a sub-population involves identifying the causal eff...
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07/05/2023
Gaussian Database Alignment and Gaussian Planted Matching
Database alignment is a variant of the graph alignment problem: Given a ...
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06/19/2023
On Identifiability of Conditional Causal Effects
We address the problem of identifiability of an arbitrary conditional ca...
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06/09/2023
A Cross-Moment Approach for Causal Effect Estimation
We consider the problem of estimating the causal effect of a treatment o...
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06/01/2023
Causal Imitability Under Context-Specific Independence Relations
Drawbacks of ignoring the causal mechanisms when performing imitation le...
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05/26/2023
Learning Causal Graphs via Monotone Triangular Transport Maps
We study the problem of causal structure learning from data using optima...
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01/26/2023
Causal Bandits without Graph Learning
We study the causal bandit problem when the causal graph is unknown and ...
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08/14/2022
Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables
We propose ordering-based approaches for learning the maximal ancestral ...
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08/09/2022
Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect
Causal identification is at the core of the causal inference literature,...
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06/02/2022
Revisiting the General Identifiability Problem
We revisit the problem of general identifiability originally introduced ...
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05/25/2022
Stochastic Second-Order Methods Provably Beat SGD For Gradient-Dominated Functions
We study the performance of Stochastic Cubic Regularized Newton (SCRN) o...
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05/20/2022
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
We study experiment design for the unique identification of the causal g...
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05/17/2022
Adaptive Momentum-Based Policy Gradient with Second-Order Information
The variance reduced gradient estimators for policy gradient methods has...
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05/04/2022
Minimum Cost Intervention Design for Causal Effect Identification
Pearl's do calculus is a complete axiomatic approach to learn the identi...
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12/20/2021
Learning Bayesian Networks in the Presence of Structural Side Information
We study the problem of learning a Bayesian network (BN) of a set of var...
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10/30/2021
Causal Discovery in Linear Structural Causal Models with Deterministic Relations
Linear structural causal models (SCMs) – in which each observed variable...
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10/22/2021
Causal Effect Identification with Context-specific Independence Relations of Control Variables
We study the problem of causal effect identification from observational ...
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10/22/2021
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...
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06/01/2021
Information Theoretic Measures for Fairness-aware Feature Selection
Machine learning algorithms are increasingly used for consequential deci...
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03/29/2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
This paper studies the complexity for finding approximate stationary poi...
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02/03/2021
Impact of Data Processing on Fairness in Supervised Learning
We study the impact of pre and post processing for reducing discriminati...
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10/10/2020
A Recursive Markov Blanket-Based Approach to Causal Structure Learning
One of the main approaches for causal structure learning is constraint-b...
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06/17/2020
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
The causal relationships among a set of random variables are commonly re...
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02/22/2020
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems
Nonconvex minimax problems appear frequently in emerging machine learnin...
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01/02/2020
Adversarial Policies in Learning Systems with Malicious Experts
We consider a learning system based on the conventional multiplicative w...
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11/12/2019
Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection
Markov blanket feature selection, while theoretically optimal, generally...
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10/28/2019
Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs
The main way for defining equivalence among acyclic directed graphs is b...
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10/12/2019
Interventional Experiment Design for Causal Structure Learning
It is known that from purely observational data, a causal DAG is identif...
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08/11/2019
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables
We consider the problem of learning causal models from observational dat...
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03/04/2019
Database Alignment with Gaussian Features
We consider the problem of aligning a pair of databases with jointly Gau...
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09/10/2018
Partial Recovery of Erdős-Rényi Graph Alignment via k-Core Alignment
We determine information theoretic conditions under which it is possible...
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06/05/2018
ScheduLeak: A Novel Scheduler Side-Channel Attack Against Real-Time Autonomous Control Systems
Real-time autonomous control systems are often the core of safety critic...
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06/04/2018
REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation
Modern real-time systems (RTS) are increasingly the focus of security th...
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05/10/2018
Fundamental Limits of Database Alignment
We consider the problem of aligning a pair of databases with correlated ...
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04/25/2018
On the Performance of a Canonical Labeling for Matching Correlated Erdős-Rényi Graphs
Graph matching in two correlated random graphs refers to the task of ide...
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02/05/2018
Counting and Uniform Sampling from Markov Equivalent DAGs
We propose an exact solution for the problem of finding the size of a Ma...
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01/25/2018
Nonparametric Hawkes Processes: Online Estimation and Generalization Bounds
In this paper, we design a nonparametric online algorithm for estimating...
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01/13/2018
Fairness in Supervised Learning: An Information Theoretic Approach
Automated decision making systems are increasingly being used in real-wo...
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09/11/2017
Budgeted Experiment Design for Causal Structure Learning
We study the problem of causal structure learning when the experimenter ...
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05/26/2017
Learning Causal Structures Using Regression Invariance
We study causal inference in a multi-environment setting, in which the f...
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05/07/2017
A Reconnaissance Attack Mechanism for Fixed-Priority Real-Time Systems
In real-time embedded systems (RTS), failures due to security breaches c...
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03/31/2017
A New Measure of Conditional Dependence
Measuring conditional dependencies among the variables of a network is o...
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02/27/2017
Learning Vector Autoregressive Models with Latent Processes
We study the problem of learning the support of transition matrix betwee...
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02/27/2017
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...
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01/30/2017
Interaction Information for Causal Inference: The Case of Directed Triangle
Interaction information is one of the multivariate generalizations of mu...
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03/14/2016
Learning Network of Multivariate Hawkes Processes: A Time Series Approach
Learning the influence structure of multiple time series data is of grea...
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09/22/2015
Efficient Neighborhood Selection for Gaussian Graphical Models
This paper addresses the problem of neighborhood selection for Gaussian ...
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04/09/2012