Research

Exploiting  Equality Constraints in Causal Inference

Chi Zhang, Carlos Cinelli, Bryant Chen, and Judea Pearl

International Conference on Artificial Intelligence and Statistics (AISTATS) 2021.

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A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models

Chi Zhang, Bryant Chen, and Judea Pearl

AAAI Conference on Artificial Intelligence (AAAI) 2020.

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Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets

Daniel Kumor, Bryant Chen, and Elias Bareinboim

Neural Information Processing Systems (NeurIPS) 2019.

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Sensitivity Analysis of Linear Structural Causal Models

Carlos Cinelli, Daniel Kumor, Bryant Chen, Elias Bareinboim, and Judea Pearl

Proceedings of the International Conference on Machine Learning (ICML) 2019.

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Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian Molloy and Biplav Srivastava

SafeAI Workshop @ AAAI 2018

Best Paper Award

Game for Detecting Backdoor Attacks on Deep Neural Networks using Activation Clustering

Casey Dugan, Werner Geyer, Aabhas Sharma, Ingrid Lange, Dustin Ramsey Torres, Bryant Chen, Nathalie Baracaldo, Heiko Ludwig​

Neural Information Processing Systems (NIPS), Demonstration, 2018

ysla: Reusable and Configurable SLAs for Large-Scale SLA Management

Robert Engel, Shashank Rajamoni, Bryant Chen, Heiko Ludwig, and Alexander Keller

IEEE Conference on Collaboration and Internet Computing (CIC), 2018

 

When Confounders are Confounded: Naive Benchmarking in Sensitivity Analysis

Carlos Cinelli, Judea Pearl, Bryant Chen

Joint Statistical Meetings, 2018

Detecting Poisoning Attacks on Machine Learning in IoT Environments

Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Amir Safavi, Rui Zhang

IEEE International Congress of Internet of Things (ICIOT), 2018 

Best Paper Award

Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance-Based Approach

Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Jaehoon Safavi

ACM Workshop on Artificial Intelligence and Security (AISEC) @ CCS 2017

Domain-Independent Monitoring and Visualization of SLA Metrics in Multi-provider Environments

Robert Engel, Bryant Chen, Shashank Rajamoni, Heiko Ludwig, Alexander Keller, Mohamed Mohamed

Proceedings of the International Conference on Cooperative Information Systems (COOPIS) 2017.

Identification and Model Testing using Auxiliary Variables

Bryant Chen, Daniel Kumor, Elias Bareinboim

Proceedings of the International Conference on Machine Learning (ICML) 2017.

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Detecting Causative Attacks using Data Provenance

Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Jaehoon Safavi

Private and Secure Machine Learning (PSML) Workshop @ ICML 2017.

Graphical Tools for Linear Path Models

Bryant Chen, Judea Pearl, Rex Kline

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Identification and Overidentification of Linear Structural Equation Models

Bryant Chen

Proceedings of Neural Information Processing Systems (NIPS) 2016.

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Incorporating Knowledge into Structural Equation Models using Auxiliary Variables

Bryant Chen, Judea Pearl, and Elias Bareinboim

Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) 2016.

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Decomposition and Identification of Linear Structural Equation Models

Bryant Chen

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Exogeneity and Robustness

Bryant Chen and Judea Pearl

Submitted.

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Graphical Tools for Linear Structural Equation Modeling

Bryant Chen and Judea Pearl

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Testable Implications of Linear Structural Equation Models

Bryant Chen, Jin Tian, and Judea Pearl

Proceedings of AAAI Conference on Artificial Intelligence 2014.

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Linear-Time Accurate Lattice Algorithms for Tail Conditional Expectation

Bryant Chen, William Hsu, Ming-Yang Kao, and Jan-Ming Ho

Algorithmic Finance 2014.

 

Regression and Causation: A Critical Examination of Econometrics Textbooks

Bryant Chen and Judea Pearl

Real-World Economics Review, Issue No. 65, 2--20, 2013

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A Game Theoretic Approach to Modeling User Behavior in Online Auctions

Damian Ancukiewicz, Bryant Chen, and Max Ohlendorf

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Integrating Diabetes Data for Analysis, Sharing, and Discovery

Nathaniel Heintzman, Bryant Chen, Tushar Dave, Lucila Ohno-Machado

AMIA Clinical Research Informatics Summit 2012

 

Fast Accurate Algorithms for Tail Conditional Expectation

Bryant Chen, William Hsu, and Ming-Yang Kao

Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2009

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Speeding Up Two-Level Simulation for Tail Conditional Expectations by Means of Prefix Sum Based Algorithms

Yi-Cheng Tsai, Hsin-Tsung Peng, Jan-Ming Ho, Bryant Chen, and Ming-Yang Kao

Proceedings of The World Congress on Engineering 2009

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