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ORCIDBabak Salimi
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- affiliation: University of California, San Diego, USA
- affiliation (former): University of Washington, Seattle, WA, USA
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2020 – today
- 2025
[i31]Parjanya Prashant, Kaustubh Ponkshe, Babak Salimi:
A Lightweight Method to Disrupt Memorized Sequences in LLM. CoRR abs/2502.05159 (2025)- 2024
- [j13]Jiongli Zhu, Babak Salimi:
Overcoming Data Biases: Towards Enhanced Accuracy and Reliability in Machine Learning. IEEE Data Eng. Bull. 47(1): 18-35 (2024) - [j12]Alireza Pirhadi
, Mohammad Hossein Moslemi, Alexander Cloninger, Mostafa Milani, Babak Salimi:
OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport. Proc. ACM Manag. Data 2(3): 160 (2024) - [c28]Jensen Hwa, Qingyu Zhao, Aditya Lahiri, Adnan Masood, Babak Salimi, Ehsan Adeli:
Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation. CVPR Workshops 2024: 103-112 - [c27]Jiongli Zhu, Su Feng, Boris Glavic, Babak Salimi:
Learning from Uncertain Data: From Possible Worlds to Possible Models. NeurIPS 2024 - [c26]Abolfazl Asudeh, Sainyam Galhotra, Amir Gilad, Babak Salimi, Brit Youngmann:
First Workshop on Governance, Understanding and Integration of Data for Effective and Responsible AI (GUIDE-AI). SIGMOD Conference Companion 2024: 661-662 - [c25]Kayvon Heravi, Saathvik Dirisala, Babak Salimi:
DEMA: Enhancing Causal Analysis through Data Enrichment and Discovery in Data Lakes. VLDB Workshops 2024 - [i30]Alireza Pirhadi, Mohammad Hossein Moslemi, Alexander Cloninger, Mostafa Milani, Babak Salimi:
OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport. CoRR abs/2403.02372 (2024) - [i29]Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi:
Graph Neural Network based Double Machine Learning Estimator of Network Causal Effects. CoRR abs/2403.11332 (2024) - [i28]Jensen Hwa, Qingyu Zhao, Aditya Lahiri, Adnan Masood, Babak Salimi, Ehsan Adeli:
Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation. CoRR abs/2404.13798 (2024) - [i27]Jiongli Zhu, Su Feng, Boris Glavic, Babak Salimi:
Learning from Uncertain Data: From Possible Worlds to Possible Models. CoRR abs/2405.18549 (2024) - [i26]Parjanya Prashant, Seyedeh Baharan Khatami, Bruno Ribeiro, Babak Salimi:
Scalable Out-of-distribution Robustness in the Presence of Unobserved Confounders. CoRR abs/2411.19923 (2024) - 2023
- [j11]Brit Youngmann, Michael J. Cafarella, Babak Salimi, Anna Zeng:
Causal Data Integration. Proc. VLDB Endow. 16(10): 2659-2665 (2023) - [j10]Jiongli Zhu, Sainyam Galhotra, Nazanin Sabri, Babak Salimi:
Consistent Range Approximation for Fair Predictive Modeling. Proc. VLDB Endow. 16(11): 2925-2938 (2023) - [c24]Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi:
On Explaining Confounding Bias. ICDE 2023: 1846-1859 - [c23]Fangzhu Shen, Kayvon Heravi, Oscar Gomez, Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi:
Causal What-If and How-To Analysis Using HypeR. ICDE 2023: 3663-3666 - [c22]Indrajit Ray, Bhavani Thuraisingham, Jaideep Vaidya, Sharad Mehrotra, Vijayalakshmi Atluri, Indrakshi Ray, Murat Kantarcioglu, Ramesh Raskar, Babak Salimi, Steve Simske, Nalini Venkatasubramanian, Vivek K. Singh:
SAFE-PASS: Stewardship, Advocacy, Fairness and Empowerment in Privacy, Accountability, Security, and Safety for Vulnerable Groups. SACMAT 2023: 145-155 - [c21]Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi:
NEXUS: On Explaining Confounding Bias. SIGMOD Conference Companion 2023: 171-174 - [i25]Brit Youngmann, Michael J. Cafarella, Babak Salimi, Anna Zeng:
Causal Data Integration. CoRR abs/2305.08741 (2023) - 2022
- [j9]Arun Kumar, Alin Deutsch, Amarnath Gupta, Yannis Papakonstantinou, Babak Salimi, Victor Vianu:
Database Education at UC San Diego. SIGMOD Rec. 51(3): 43-46 (2022) - [c20]Romila Pradhan, Aditya Lahiri, Sainyam Galhotra, Babak Salimi:
Explainable AI: Foundations, Applications, Opportunities for Data Management Research. ICDE 2022: 3209-3212 - [c19]Sudeepa Roy, Babak Salimi:
Causal Inference in Data Analysis with Applications to Fairness and Explanations. RW 2022: 105-131 - [c18]Maliha Tashfia Islam, Anna Fariha, Alexandra Meliou, Babak Salimi:
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification. SIGMOD Conference 2022: 232-246 - [c17]Romila Pradhan, Jiongli Zhu, Boris Glavic, Babak Salimi:
Interpretable Data-Based Explanations for Fairness Debugging. SIGMOD Conference 2022: 247-261 - [c16]Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi:
HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach. SIGMOD Conference 2022: 1598-1611 - [c15]Jiongli Zhu, Romila Pradhan, Boris Glavic, Babak Salimi:
Generating Interpretable Data-Based Explanations for Fairness Debugging using Gopher. SIGMOD Conference 2022: 2433-2436 - [c14]Romila Pradhan, Aditya Lahiri, Sainyam Galhotra, Babak Salimi:
Explainable AI: Foundations, Applications, Opportunities for Data Management Research. SIGMOD Conference 2022: 2452-2457 - [i24]Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi:
HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach. CoRR abs/2203.14692 (2022) - [i23]Kamran Alipour, Aditya Lahiri, Ehsan Adeli, Babak Salimi, Michael J. Pazzani:
Explaining Image Classifiers Using Contrastive Counterfactuals in Generative Latent Spaces. CoRR abs/2206.05257 (2022) - [i22]Aditya Lahiri, Kamran Alipour, Ehsan Adeli, Babak Salimi:
Combining Counterfactuals With Shapley Values To Explain Image Models. CoRR abs/2206.07087 (2022) - [i21]Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi:
On Explaining Confounding Bias. CoRR abs/2210.02943 (2022) - [i20]Jiongli Zhu, Nazanin Sabri, Sainyam Galhotra, Babak Salimi:
Crab: Learning Certifiably Fair Predictive Models in the Presence of Selection Bias. CoRR abs/2212.10839 (2022) - 2021
- [j8]Paul Y. Wang, Sainyam Galhotra, Romila Pradhan, Babak Salimi:
Demonstration of Generating Explanations for Black-Box Algorithms Using Lewis. Proc. VLDB Endow. 14(12): 2787-2790 (2021) - [c13]Sainyam Galhotra, Romila Pradhan, Babak Salimi:
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals. SIGMOD Conference 2021: 577-590 - [i19]Sainyam Galhotra, Romila Pradhan, Babak Salimi:
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals. CoRR abs/2103.11972 (2021) - [i18]Amir Gilad, Harsh Parikh, Babak Salimi, Sudeepa Roy:
Detecting Treatment Effect Modifiers in Social Networks. CoRR abs/2105.10591 (2021) - [i17]Romila Pradhan, Jiongli Zhu, Boris Glavic, Babak Salimi:
Interpretable Data-Based Explanations for Fairness Debugging. CoRR abs/2112.09745 (2021) - 2020
- [j7]Moe Kayali, Babak Salimi, Dan Suciu:
Demonstration of Inferring Causality from Relational Databases with CaRL. Proc. VLDB Endow. 13(12): 2985-2988 (2020) - [j6]Babak Salimi, Bill Howe, Dan Suciu:
Database Repair Meets Algorithmic Fairness. SIGMOD Rec. 49(1): 34-41 (2020) - [c12]Babak Salimi, Harsh Parikh, Moe Kayali, Lise Getoor, Sudeepa Roy, Dan Suciu:
Causal Relational Learning. SIGMOD Conference 2020: 241-256 - [c11]Batya Kenig, Pranay Mundra, Guna Prasaad, Babak Salimi, Dan Suciu:
Mining Approximate Acyclic Schemes from Relations. SIGMOD Conference 2020: 297-312 - [i16]Babak Salimi, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, Dan Suciu:
Causal Relational Learning. CoRR abs/2004.03644 (2020)
2010 – 2019
- 2019
- [j5]Babak Salimi, Bill Howe, Dan Suciu:
Data Management for Causal Algorithmic Fairness. IEEE Data Eng. Bull. 42(3): 24-35 (2019) - [c10]Babak Salimi, Luke Rodriguez, Bill Howe, Dan Suciu:
Interventional Fairness: Causal Database Repair for Algorithmic Fairness. SIGMOD Conference 2019: 793-810 - [i15]Babak Salimi, Luke Rodriguez, Bill Howe, Dan Suciu:
Capuchin: Causal Database Repair for Algorithmic Fairness. CoRR abs/1902.08283 (2019) - [i14]Babak Salimi, Bill Howe, Dan Suciu:
Data Management for Causal Algorithmic Fairness. CoRR abs/1908.07924 (2019) - [i13]Batya Kenig, Pranay Mundra, Guna Prasaad, Babak Salimi, Dan Suciu:
Mining Approximate Acyclic Schemes from Relations. CoRR abs/1911.12933 (2019) - 2018
- [j4]Babak Salimi, Corey Cole, Peter Li, Johannes Gehrke, Dan Suciu:
HypDB: A Demonstration of Detecting, Explaining and Resolving Bias in OLAP queries. Proc. VLDB Endow. 11(12): 2062-2065 (2018) - [c9]Babak Salimi, Johannes Gehrke, Dan Suciu:
Bias in OLAP Queries: Detection, Explanation, and Removal. SIGMOD Conference 2018: 1021-1035 - [c8]Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, Bill Howe:
MobilityMirror: Bias-Adjusted Transportation Datasets. BiDU@VLDB 2018: 18-39 - [i12]Babak Salimi, Johannes Gehrke, Dan Suciu:
HypDB: Detect, Explain And Resolve Bias in OLAP. CoRR abs/1803.04562 (2018) - [i11]Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, Bill Howe:
MobilityMirror: Bias-Adjusted Transportation Datasets. CoRR abs/1808.07151 (2018) - 2017
- [j3]Leopoldo E. Bertossi, Babak Salimi:
Causes for query answers from databases: Datalog abduction, view-updates, and integrity constraints. Int. J. Approx. Reason. 90: 226-252 (2017) - [j2]Leopoldo E. Bertossi, Babak Salimi:
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back. Theory Comput. Syst. 61(1): 191-232 (2017) - [j1]Babak Salimi, Corey Cole, Dan R. K. Ports, Dan Suciu:
ZaliQL: Causal Inference from Observational Data at Scale. Proc. VLDB Endow. 10(12): 1957-1960 (2017) - [c7]Helga Gudmundsdottir, Babak Salimi, Magdalena Balazinska, Dan R. K. Ports, Dan Suciu:
A Demonstration of Interactive Analysis of Performance Measurements with Viska. SIGMOD Conference 2017: 1707-1710 - [i10]Sudeepa Roy, Babak Salimi:
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence. CoRR abs/1708.02536 (2017) - 2016
- [c6]Babak Salimi, Leopoldo E. Bertossi:
Causes for Query Answers from Databases, Datalog Abduction and View-Updates: The Presence of Integrity Constraints. FLAIRS 2016: 674-679 - [c5]Babak Salimi, Leopoldo E. Bertossi, Dan Suciu, Guy Van den Broeck:
Quantifying Causal Effects on Query Answering in Databases. TaPP 2016 - [i9]Babak Salimi, Leopoldo E. Bertossi:
Causes for Query Answers from Databases, Datalog Abduction and View-Updates: The Presence of Integrity Constraints. CoRR abs/1602.06458 (2016) - [i8]Babak Salimi, Leopoldo E. Bertossi, Dan Suciu, Guy Van den Broeck:
Quantifying Causal Effects on Query Answering in Databases. CoRR abs/1603.02705 (2016) - [i7]Babak Salimi, Dan Suciu:
ZaliQL: A SQL-Based Framework for Drawing Causal Inference from Big Data. CoRR abs/1609.03540 (2016) - [i6]Leopoldo E. Bertossi, Babak Salimi:
Causes for Query Answers from Databases: Datalog Abduction, View-Updates, and Integrity Constraints. CoRR abs/1611.01711 (2016) - 2015
- [c4]Babak Salimi, Leopoldo E. Bertossi:
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back. ICDT 2015: 342-362 - [c3]Babak Salimi, Leopoldo E. Bertossi:
Query-Answer Causality in Databases: Abductive Diagnosis and View Updates. ACI@UAI 2015: 76-85 - [i5]Babak Salimi, Leopoldo E. Bertossi:
Query-Answer Causality in Databases: Abductive Diagnosis and View-Updates. CoRR abs/1506.04299 (2015) - [i4]Babak Salimi, Leopoldo E. Bertossi:
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back. CoRR abs/1507.00257 (2015) - 2014
- [c2]Leopoldo E. Bertossi, Babak Salimi:
Causality in Databases, Database Repairs, and Consistency-Based Diagnosis (extended abstract). AMW 2014 - [i3]Babak Salimi, Leopoldo E. Bertossi:
Causality in Databases: The Diagnosis and Repair Connections. CoRR abs/1404.6857 (2014) - [i2]Leopoldo E. Bertossi, Babak Salimi:
Unifying Causality, Diagnosis, Repairs and View-Updates in Databases. CoRR abs/1405.4228 (2014) - [i1]Babak Salimi, Leopoldo E. Bertossi:
From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back. CoRR abs/1412.4311 (2014)
1990 – 1999
- 1990
- [c1]Janusz Rajski, Jerzy Tyszer, Babak Salimi:
On the Diagnostic Resolution of Signature Analysis. ICCAD 1990: 364-367
Coauthor Index
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