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Lakkaraju, Himabindu Remove Lakkaraju, Himabindu →

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  • 2020
  • Article

Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods.
By: Dylan Slack, Sophie Hilgard, Emily Jia, Sameer Singh and Himabindu Lakkaraju
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  • 2020
  • Article

"How Do I Fool You?": Manipulating User Trust via Misleading Black Box Explanations
By: Himabindu Lakkaraju and Osbert Bastani
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  • Article

Human Decisions and Machine Predictions
By: Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig and Sendhil Mullainathan
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  • Article

The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables
By: Himabindu Lakkaraju, Jon Kleinberg, Jure Leskovec, Jens Ludwig and Sendhil Mullainathan
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  • Article

Learning Cost-Effective and Interpretable Treatment Regimes
By: Himabindu Lakkaraju and Cynthia Rudin
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  • Article

Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration
By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Eric Horvitz
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  • 9 Dec 2016
  • Conference Presentation

Discovering Unknown Unknowns of Predictive Models
By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Eric Horvitz
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  • 9 Dec 2016
  • Conference Presentation

Learning Cost-Effective and Interpretable Regimes for Treatment Recommendation
By: Himabindu Lakkaraju and Cynthia Rudin
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  • 8 Dec 2016
  • Conference Presentation

Learning Cost-Effective and Interpretable Treatment Regimes for Judicial Bail Decisions
By: Himabindu Lakkaraju and Cynthia Rudin
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  • Article

Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making
By: Himabindu Lakkaraju and Jure Leskovec
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  • Article

Interpretable Decision Sets: A Joint Framework for Description and Prediction
By: Himabindu Lakkaraju, Stephen H. Bach and Jure Leskovec
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  • Article

Mining Big Data to Extract Patterns and Predict Real-Life Outcomes
By: Michal Kosinki, Yilun Wang, Himabindu Lakkaraju and Jure Leskovec
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  • 2015
  • Article

A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes
By: Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani and Kecia Addison
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  • 2015
  • Article

A Bayesian Framework for Modeling Human Evaluations
By: Himabindu Lakkaraju, Jure Leskovec, Jon Kleinberg and Sendhil Mullainathan
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  • Article

Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time
By: Everaldo Aguiar, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia Addison and Rayid Ghani
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  • 12 Dec 2014
  • Conference Presentation

Aspect Specific Sentiment Analysis Using Hierarchical Deep Learning
By: Himabindu Lakkaraju, Richard Socher and Chris Manning
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  • 2014
  • Other Unpublished Work

Using Big Data to Improve Social Policy
By: Himabindu Lakkaraju, Jon Kleinberg, Jure Leskovec, Jens Ludwig and Sendhil Mullainathan
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  • Article

What's in a Name? Understanding the Interplay Between Titles, Content, and Communities in Social Media
By: Himabindu Lakkaraju, Julian McAuley and Jure Leskovec
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  • Article

Dynamic Multi-Relational Chinese Restaurant Process for Analyzing Influences on Users in Social Media
By: Himabindu Lakkaraju, Indrajit Bhattacharya and Chiranjib Bhattacharyya
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  • Article

TEM: A Novel Perspective to Modeling Content on Microblogs
By: Himabindu Lakkaraju and Hyung-Il Ahn
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