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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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05/27/2022
Fast Causal Orientation Learning in Directed Acyclic Graphs
Causal relationships among a set of variables are commonly represented b...
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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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12/07/2021
Causal Imitative Model for Autonomous Driving
Imitation learning is a powerful approach for learning autonomous drivin...
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09/28/2021
ParaLiNGAM: Parallel Causal Structure Learning for Linear non-Gaussian Acyclic Models
One of the key objectives in many fields in machine learning is to disco...
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08/19/2021
Order Optimal One-Shot Federated Learning for non-Convex Loss Functions
We consider the problem of federated learning in a one-shot setting in w...
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09/16/2020
Deep-Learning Based Blind Recognition of Channel Code Parameters over Candidate Sets under AWGN and Multi-Path Fading Conditions
We consider the problem of recovering channel code parameters over a can...
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09/15/2020
GPU Accelerated RIS-based Influence Maximization Algorithm
Given a social network modeled as a weighted graph G, the influence maxi...
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09/07/2020
Active Learning of Causal Structures with Deep Reinforcement Learning
We study the problem of experiment design to learn causal structures fro...
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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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11/02/2019
Order Optimal One-Shot Distributed Learning
We consider distributed statistical optimization in one-shot setting, wh...
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10/22/2019
Distributed Voting in Beep Model
In this paper, we propose two distributed algorithms, named Distributed ...
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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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09/10/2019
Adversarial Orthogonal Regression: Two non-Linear Regressions for Causal Inference
We propose two nonlinear regression methods, named Adversarial Orthogona...
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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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07/16/2019
Broadcast Distributed Voting Algorithm in Population Protocols
We consider the problem of multi-choice majority voting in a network of ...
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07/15/2019
Seedless Graph Matching via Tail of Degree Distribution for Correlated Erdos-Renyi Graphs
The graph matching problem refers to recovering the node-to-node corresp...
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05/12/2019
Theoretical Limits of One-Shot Distributed Learning
We consider a distributed system of m machines and a server. Each machin...
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12/20/2018
cuPC: CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU
The main goal in many fields in empirical sciences is to discover causal...
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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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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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03/26/2017
Token-based Function Computation with Memory
In distributed function computation, each node has an initial value and ...
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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
