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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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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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05/04/2022
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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02/18/2022
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics
Parameter estimation in the empirical fields is usually undertaken using...
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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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10/22/2021
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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05/25/2020
Non-cooperative Multi-agent Systems with Exploring Agents
Multi-agent learning is a challenging problem in machine learning that h...
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03/02/2020
Causal Transfer for Imitation Learning and Decision Making under Sensor-shift
Learning from demonstrations (LfD) is an efficient paradigm to train AI ...
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06/19/2019
Wasserstein Adversarial Imitation Learning
Imitation Learning describes the problem of recovering an expert policy ...
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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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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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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
