Shalmali Joshi

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 42

Top Topics

Feature Importance

Machine Learning

Differentially Private

Top Venues

Publications

Shalmali Joshi, Junzhe Zhang, Elias Bareinboim
Towards Safe Policy Learning under Partial Identifiability: A Causal Approach. AAAI (2024)
Daniel Ehrmann, Shalmali Joshi, Sebastian D. Goodfellow, Mjaye Mazwi, Danny Eytan
Making machine learning matter to clinicians: model actionability in medical decision-making. npj Digit. Medicine 6 (2023)
Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
Learning-to-defer for sequential medical decision-making under uncertainty. Trans. Mach. Learn. Res. 2023 (2023)
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML (2023)
Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Alex John London
A normative framework for artificial intelligence as a sociotechnical system in healthcare. Patterns 4 (11) (2023)
Melissa D. McCradden, Oluwadara Odusi, Shalmali Joshi, Ismail Akrout, Kagiso Ndlovu, Ben Glocker, Gabriel Maicas, Xiaoxuan Liu, Mjaye Mazwi, Tee Garnett, Lauren Oakden-Rayner, Myrtede Alfred, Irvine Sihlahla, Oswa Shafei, Anna Goldenberg
What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB. FAccT (2023)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Towards Robust Off-Policy Evaluation via Human Inputs. AIES (2022)
Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi
Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS (2022)
Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez
Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. CoRR (2022)
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR (2022)
Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi
Counterfactually Guided Policy Transfer in Clinical Settings. CHIL (2022)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Towards Robust Off-Policy Evaluation via Human Inputs. CoRR (2022)
Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy
Machine Learning for Health symposium 2022 - Extended Abstract track. CoRR (2022)
Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis. AISTATS (2022)
Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CoRR (2021)
Martin Pawelczyk, Shalmali Joshi, Chirag Agarwal, Sohini Upadhyay, Himabindu Lakkaraju
On the Connections between Counterfactual Explanations and Adversarial Examples. CoRR (2021)
Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CIKM (2021)
Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. FAccT (2021)
Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
An Empirical Framework for Domain Generalization in Clinical Settings. CoRR (2021)
Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
Towards Robust and Reliable Algorithmic Recourse. NeurIPS (2021)
Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
An empirical framework for domain generalization in clinical settings. CHIL (2021)
Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
Towards Robust and Reliable Algorithmic Recourse. CoRR (2021)
Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. CoRR (2021)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Learning Under Adversarial and Interventional Shifts. CoRR (2021)
Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi
Ethical Machine Learning in Health Care. CoRR (2020)
Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David Duvenaud, Anna Goldenberg
What went wrong and when? Instance-wise feature importance for time-series black-box models. NeurIPS (2020)
Sana Tonekaboni, Shalmali Joshi, David Duvenaud, Anna Goldenberg
What went wrong and when? Instance-wise Feature Importance for Time-series Models. CoRR (2020)
Arnold Y. S. Yeung, Shalmali Joshi, Joseph Jay Williams, Frank Rudzicz
Sequential Explanations with Mental Model-Based Policies. CoRR (2020)
Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi
Confounding Feature Acquisition for Causal Effect Estimation. ML4H@NeurIPS (2020)
Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath
Probabilistic Machine Learning for Healthcare. CoRR (2020)
Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi
Counterfactually Guided Policy Transfer in Clinical Settings. CoRR (2020)
Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. J. Am. Medical Informatics Assoc. 27 (12) (2020)
Melissa D. McCradden, Mjaye Mazwi, Shalmali Joshi, James A. Anderson
When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning. AIES (2020)
Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi
Confounding Feature Acquisition for Causal Effect Estimation. CoRR (2020)
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. CoRR (2019)
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. MLHC (2019)
Shalmali Joshi, Oluwasanmi Koyejo, Warut Vijitbenjaronk, Been Kim, Joydeep Ghosh
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. CoRR (2019)
Shalmali Joshi, Rajiv Khanna, Joydeep Ghosh
Co-regularized Monotone Retargeting for Semi-supervised LeTOR. SDM (2018)
Shalmali Joshi, Oluwasanmi Koyejo, Been Kim, Joydeep Ghosh
xGEMs: Generating Examplars to Explain Black-Box Models. CoRR (2018)
Shalmali Joshi, Suriya Gunasekar, David A. Sontag, Joydeep Ghosh
Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. MLHC (2016)
Shalmali Joshi, Suriya Gunasekar, David A. Sontag, Joydeep Ghosh
Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. CoRR (2016)
Shalmali Joshi, Joydeep Ghosh, Mark Reid, Oluwasanmi Koyejo
Rényi divergence minimization based co-regularized multiview clustering. Mach. Learn. 104 (2-3) (2016)
Shalmali Joshi, Oluwasanmi Koyejo, Joydeep Ghosh
Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data. ICHI (2015)
Shalmali Joshi, Oluwasanmi Koyejo, Kristine Resurreccion, Joydeep Ghosh
Simultaneous Prognosis and Exploratory Analysis of Multiple Chronic Conditions Using Clinical Notes. ICHI (2015)