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Adam Tauman Kalai

Microsoft Research

Social Norm Bias: Residual Harms of Fairness-Aware Algorithms


Aug 29, 2021
Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai

* Spotlighted at the 2021 ICML Machine Learning for Data Workshop and presented at the 2021 ICML Socially Responsible Machine Learning Workshop 

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Programming Puzzles


Jun 10, 2021
Tal Schuster, Ashwin Kalyan, Oleksandr Polozov, Adam Tauman Kalai

* The puzzles repo: https://github.com/microsoft/PythonProgrammingPuzzles 

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Towards optimally abstaining from prediction


May 28, 2021
Adam Tauman Kalai, Varun Kanade

* 23 pages 

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Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples


Jul 10, 2020
Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser


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Learning to Prune: Speeding up Repeated Computations


Apr 26, 2019
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik


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What's in a Name? Reducing Bias in Bios without Access to Protected Attributes


Apr 10, 2019
Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai

* Accepted at NAACL 2019; Best Thematic Paper 

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Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops


Feb 11, 2019
Limor Gultchin, Genevieve Patterson, Nancy Baym, Nathaniel Swinger, Adam Tauman Kalai


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Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting


Jan 27, 2019
Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai

* Accepted at ACM Conference on Fairness, Accountability, and Transparency (ACM FAT*), 2019 

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What are the biases in my word embedding?


Dec 22, 2018
Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark DM Leiserson, Adam Tauman Kalai

* At AIES 2019: the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 

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Unleashing Linear Optimizers for Group-Fair Learning and Optimization


Jun 04, 2018
Daniel Alabi, Nicole Immorlica, Adam Tauman Kalai

* Accepted for presentation at the Conference on Learning Theory (COLT) 2018 

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Glass-Box Program Synthesis: A Machine Learning Approach


Sep 25, 2017
Konstantina Christakopoulou, Adam Tauman Kalai


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Decoupled classifiers for fair and efficient machine learning


Jul 20, 2017
Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Max Leiserson


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Meta-Unsupervised-Learning: A supervised approach to unsupervised learning


Jan 03, 2017
Vikas K. Garg, Adam Tauman Kalai

* 22 pages 

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Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons


Mar 31, 2015
James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai


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Textual Features for Programming by Example


Sep 17, 2012
Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai


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Adaptively Learning the Crowd Kernel


Jun 25, 2011
Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, Adam Tauman Kalai

* The 28th International Conference on Machine Learning, 2011 
* 9 pages, 7 figures, Accepted to the 28th International Conference on Machine Learning (ICML), 2011 

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Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression


Apr 11, 2011
Sham Kakade, Adam Tauman Kalai, Varun Kanade, Ohad Shamir


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Decision trees are PAC-learnable from most product distributions: a smoothed analysis


Dec 04, 2008
Adam Tauman Kalai, Shang-Hua Teng


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Online convex optimization in the bandit setting: gradient descent without a gradient


Aug 02, 2004
Abraham D. Flaxman, Adam Tauman Kalai, H. Brendan McMahan

* 12 pages 

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