Adam Tauman Kalai

According to our database, Adam Tauman Kalai authored at least 112 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Beyond dominance and Nash: Ranking equilibria by critical mass.

Adam Tauman Kalai, Ehud Kalai

Games Econ. Behav., 2024

First-Person Fairness in Chatbots.

Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu-Lemberg, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai

CoRR, 2024

Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding.

Mirac Suzgun, Adam Tauman Kalai

CoRR, 2024

Calibrated Language Models Must Hallucinate.

Adam Tauman Kalai, Santosh S. Vempala

Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024

Loss Minimization Yields Multicalibration for Large Neural Networks.

Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Adam Tauman Kalai, Preetum Nakkiran

Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

Do Language Models Know When They're Hallucinating References?

Ayush Agrawal, Mirac Suzgun, Lester Mackey, Adam Kalai

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023

Social norm bias: residual harms of fairness-aware algorithms.

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

Data Min. Knowl. Discov., September, 2023

Testing Language Model Agents Safely in the Wild.

Silen Naihin, David Atkinson, Marc Green, Merwane Hamadi, Craig Swift, Douglas Schonholtz, Adam Tauman Kalai, David Bau

CoRR, 2023

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation.

Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai

CoRR, 2023

Textbooks Are All You Need.

Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li

CoRR, 2023

Do Language Models Know When They're Hallucinating References?

Ayush Agrawal, Lester Mackey, Adam Tauman Kalai

CoRR, 2023

Partial Matrix Completion.

Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Theory of Unsupervised Translation Motivated by Understanding Animal Communication.

Shafi Goldwasser, David F. Gruber, Adam Tauman Kalai, Orr Paradise

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies.

Gati V. Aher, Rosa I. Arriaga, Adam Tauman Kalai

Proceedings of the International Conference on Machine Learning, 2023

Language Models Can Teach Themselves to Program Better.

Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Comparing Different Approaches to Generating Mathematics Explanations Using Large Language Models.

Ethan Prihar, Morgan P. Lee, Mia Hopman, Adam Tauman Kalai, Sofia Vempala, Allison Wang, Gabriel Wickline, Aly Murray, Neil T. Heffernan

Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, 2023

2022

Partial Matrix Completion.

Varun Kanade, Elad Hazan, Adam Tauman Kalai

CoRR, 2022

Using Large Language Models to Simulate Multiple Humans.

Gati Aher, Rosa I. Arriaga, Adam Tauman Kalai

CoRR, 2022

Why GANs are overkill for NLP.

David Alvarez-Melis, Vikas Garg, Adam Tauman Kalai

CoRR, 2022

Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms.

Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Are GANs overkill for NLP?

David Alvarez-Melis, Vikas Garg, Adam Kalai

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Omnipredictors.

Parikshit Gopalan, Adam Tauman Kalai, Omer Reingold, Vatsal Sharan, Udi Wieder

Proceedings of the 13th Innovations in Theoretical Computer Science Conference, 2022

2021

Towards optimally abstaining from prediction.

Adam Tauman Kalai, Varun Kanade

CoRR, 2021

Programming Puzzles.

Tal Schuster, Ashwin Kalyan, Alex Polozov, Adam Kalai

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Towards optimally abstaining from prediction with OOD test examples.

Adam Kalai, Varun Kanade

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Learning with Arbitrary Covariate Shift.

Adam Tauman Kalai, Varun Kanade

Proceedings of the Algorithmic Learning Theory, 2021

Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization.

Vikas K. Garg, Adam Tauman Kalai, Katrina Ligett, Zhiwei Steven Wu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples.

Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

HAI-GEN 2020: Workshop on Human-AI Co-Creation with Generative Models.

Werner Geyer, Lydia B. Chilton, Ranjitha Kumar, Adam Tauman Kalai

Proceedings of the IUI '20: 25th International Conference on Intelligent User Interfaces, 2020

Identifying unpredictable test examples with worst-case guarantees.

Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser

Proceedings of the Information Theory and Applications Workshop, 2020

The disparate equilibria of algorithmic decision making when individuals invest rationally.

Lydia T. Liu, Ashia Wilson, Nika Haghtalab, Adam Tauman Kalai, Christian Borgs, Jennifer T. Chayes

Proceedings of the FAT* '20: Conference on Fairness, 2020

2019

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

Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops.

Limor Gultchin, Genevieve Patterson, Nancy Baym, Nathaniel Swinger, Adam Kalai

Proceedings of the 36th International Conference on Machine Learning, 2019

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

Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Learning to Prune: Speeding up Repeated Computations.

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

Proceedings of the Conference on Learning Theory, 2019

Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning.

Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni

Proceedings of the Algorithmic Learning Theory, 2019

What are the Biases in My Word Embedding?

Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Algorithmic Greenlining: An Approach to Increase Diversity.

Christian Borgs, Jennifer T. Chayes, Nika Haghtalab, Adam Tauman Kalai, Ellen Vitercik

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

When optimizing nonlinear objectives is no harder than linear objectives.

Daniel Alabi, Nicole Immorlica, Adam Tauman Kalai

CoRR, 2018

Usability of Humanly Computable Passwords.

Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai

Proceedings of the Sixth AAAI Conference on Human Computation and Crowdsourcing, 2018

Decoupled Classifiers for Group-Fair and Efficient Machine Learning.

Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Mark D. M. Leiserson

Proceedings of the Conference on Fairness, Accountability and Transparency, 2018

Actively Avoiding Nonsense in Generative Models.

Steve Hanneke, Adam Tauman Kalai, Gautam Kamath, Christos Tzamos

Proceedings of the Conference On Learning Theory, 2018

Unleashing Linear Optimizers for Group-Fair Learning and Optimization.

Daniel Alabi, Nicole Immorlica, Adam Kalai

Proceedings of the Conference On Learning Theory, 2018

Glass-Box Program Synthesis: A Machine Learning Approach.

Konstantina Christakopoulou, Adam Tauman Kalai

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Supervising Unsupervised Learning.

Vikas K. Garg, Adam Kalai

CoRR, 2017

Decoupled classifiers for fair and efficient machine learning.

Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Max D. M. Leiserson

CoRR, 2017

Designing and Evaluating Livefonts.

Danielle Bragg, Shiri Azenkot, Kevin Larson, Ann Bessemans, Adam Tauman Kalai

Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, 2017

Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context.

Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Kalai, James Y. Zou

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Counterfactual Language Model Adaptation for Suggesting Phrases.

Kenneth C. Arnold, Kai-Wei Chang, Adam Kalai

Proceedings of the Eighth International Joint Conference on Natural Language Processing, 2017

Learning to Suggest Phrases.

Kenneth Charles Arnold, Kai-Wei Chang, Adam Tauman Kalai

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

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

Vikas K. Garg, Adam Tauman Kalai

CoRR, 2016

Quantifying and Reducing Stereotypes in Word Embeddings.

Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai

CoRR, 2016

Reading and Learning Smartfonts.

Danielle Bragg, Shiri Azenkot, Adam Tauman Kalai

Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 2016

On Suggesting Phrases vs. Predicting Words for Mobile Text Composition.

Kenneth C. Arnold, Krzysztof Z. Gajos, Adam Tauman Kalai

Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 2016

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.

Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Matching and Grokking: Approaches to Personalized Crowdsourcing.

Peter Organisciak, Jaime Teevan, Susan T. Dumais, Robert C. Miller, Adam Tauman Kalai

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

OMG UR Funny! Computer-Aided Humor with an Application to Chat.

Miaomiao Wen, Nancy Baym, Omer Tamuz, Jaime Teevan, Susan T. Dumais, Adam Kalai

Proceedings of the Sixth International Conference on Computational Creativity, 2015

Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons.

James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai

Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

2014

A Crowd of Your Own: Crowdsourcing for On-Demand Personalization.

Peter Organisciak, Jaime Teevan, Susan T. Dumais, Robert C. Miller, Adam Tauman Kalai

Proceedings of the Seconf AAAI Conference on Human Computation and Crowdsourcing, 2014

2013

A colorful approach to text processing by example.

Kuat Yessenov, Shubham Tulsiani, Aditya Krishna Menon, Robert C. Miller, Sumit Gulwani, Butler W. Lampson, Adam Kalai

Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, 2013

Feature Multi-Selection among Subjective Features.

Sivan Sabato, Adam Kalai

Proceedings of the 30th International Conference on Machine Learning, 2013

A Machine Learning Framework for Programming by Example.

Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler W. Lampson, Adam Kalai

Proceedings of the 30th International Conference on Machine Learning, 2013

Personalized Human Computation.

Peter Organisciak, Jaime Teevan, Susan T. Dumais, Robert C. Miller, Adam Tauman Kalai

Proceedings of the Human Computation and Crowdsourcing: Works in Progress and Demonstration Abstracts, 2013

2012

Reliable agnostic learning.

Adam Tauman Kalai, Varun Kanade, Yishay Mansour

J. Comput. Syst. Sci., 2012

Textual Features for Programming by Example

Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler W. Lampson, Adam Tauman Kalai

CoRR, 2012

Disentangling Gaussians.

Adam Tauman Kalai, Ankur Moitra, Gregory Valiant

Commun. ACM, 2012

2011

Cooperation in two person games, revisited.

Adam Kalai, Ehud Kalai

SIGecom Exch., 2011

Dueling algorithms.

Nicole Immorlica, Adam Tauman Kalai, Brendan Lucier, Ankur Moitra, Andrew Postlewaite, Moshe Tennenholtz

Proceedings of the 43rd ACM Symposium on Theory of Computing, 2011

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

Sham M. Kakade, Adam Kalai, Varun Kanade, Ohad Shamir

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Compression without a common prior: an information-theoretic justification for ambiguity in language.

Brendan Juba, Adam Tauman Kalai, Sanjeev Khanna, Madhu Sudan

Proceedings of the Innovations in Computer Science, 2011

Adaptively Learning the Crowd Kernel.

Omer Tamuz, Ce Liu, Serge J. Belongie, Ohad Shamir, Adam Kalai

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

A commitment folk theorem.

Adam Tauman Kalai, Ehud Kalai, Ehud Lehrer, Dov Samet

Games Econ. Behav., 2010

A Novel Approach to Propagating Distrust.

Christian Borgs, Jennifer T. Chayes, Adam Tauman Kalai, Azarakhsh Malekian, Moshe Tennenholtz

Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

Efficiently learning mixtures of two Gaussians.

Adam Tauman Kalai, Ankur Moitra, Gregory Valiant

Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

On the Equilibria of Alternating Move Games.

Aaron Roth, Maria-Florina Balcan, Adam Kalai, Yishay Mansour

Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

Cooperation and competition in strategic games with private information.

Adam Tauman Kalai, Ehud Kalai

Proceedings of the Proceedings 11th ACM Conference on Electronic Commerce (EC-2010), 2010

Tight asymptotic bounds for the deletion channel with small deletion probabilities.

Adam Kalai, Michael Mitzenmacher, Madhu Sudan

Proceedings of the IEEE International Symposium on Information Theory, 2010

Playing Games without Observing Payoffs.

Michal Feldman, Adam Kalai, Moshe Tennenholtz

Proceedings of the Innovations in Computer Science, 2010

2009

Playing Games with Approximation Algorithms.

Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett

SIAM J. Comput., 2009

Analysis of Perceptron-Based Active Learning.

Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni

J. Mach. Learn. Res., 2009

Potential-Based Agnostic Boosting.

Adam Kalai, Varun Kanade

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Learning and Smoothed Analysis.

Adam Tauman Kalai, Alex Samorodnitsky, Shang-Hua Teng

Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science, 2009

The Isotron Algorithm: High-Dimensional Isotonic Regression.

Adam Tauman Kalai, Ravi Sastry

Proceedings of the COLT 2009, 2009

2008

Agnostically Learning Halfspaces.

Adam Tauman Kalai, Adam R. Klivans, Yishay Mansour, Rocco A. Servedio

SIAM J. Comput., 2008

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

Adam Tauman Kalai, Shang-Hua Teng

CoRR, 2008

Trust-based recommendation systems: an axiomatic approach.

Reid Andersen, Christian Borgs, Jennifer T. Chayes, Uriel Feige, Abraham D. Flaxman, Adam Kalai, Vahab S. Mirrokni, Moshe Tennenholtz

Proceedings of the 17th International Conference on World Wide Web, 2008

On agnostic boosting and parity learning.

Adam Tauman Kalai, Yishay Mansour, Elad Verbin

Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Agnostically learning decision trees.

Parikshit Gopalan, Adam Tauman Kalai, Adam R. Klivans

Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

A Query Algorithm for Agnostically Learning DNF?.

Parikshit Gopalan, Adam Kalai, Adam R. Klivans

Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007

The Myth of the Folk Theorem.

Christian Borgs, Jennifer T. Chayes, Nicole Immorlica, Adam Kalai, Vahab S. Mirrokni, Christos H. Papadimitriou

Electron. Colloquium Comput. Complex., 2007

Learning Nested Halfspaces and Uphill Decision Trees.

Adam Tauman Kalai

Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006

Simulated Annealing for Convex Optimization.

Adam Tauman Kalai, Santosh S. Vempala

Math. Oper. Res., 2006

An Approach to Bounded Rationality.

Eli Ben-Sasson, Adam Tauman Kalai, Ehud Kalai

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Graph model selection using maximum likelihood.

Ivona Bezáková, Adam Kalai, Rahul Santhanam

Proceedings of the Machine Learning, 2006

Logarithmic Regret Algorithms for Online Convex Optimization.

Elad Hazan, Adam Kalai, Satyen Kale, Amit Agarwal

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005

Efficient algorithms for online decision problems.

Adam Tauman Kalai, Santosh S. Vempala

J. Comput. Syst. Sci., 2005

Boosting in the presence of noise.

Adam Tauman Kalai, Rocco A. Servedio

J. Comput. Syst. Sci., 2005

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

Abraham Flaxman, Adam Tauman Kalai, H. Brendan McMahan

Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2005

From Batch to Transductive Online Learning.

Sham M. Kakade, Adam Kalai

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004

Learning Monotonic Linear Functions.

Adam Kalai

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003

Generating Random Factored Numbers, Easily.

Adam Kalai

J. Cryptol., 2003

Noise-tolerant learning, the parity problem, and the statistical query model.

Avrim Blum, Adam Kalai, Hal Wasserman

J. ACM, 2003

Admission Control to Minimize Rejections.

Avrim Blum, Adam Tauman Kalai, Jon M. Kleinberg

Internet Math., 2003

Static Optimality and Dynamic Search-Optimality in Lists and Trees.

Avrim Blum, Shuchi Chawla, Adam Kalai

Algorithmica, 2003

2002

Efficient Algorithms for Universal Portfolios.

Adam Kalai, Santosh S. Vempala

J. Mach. Learn. Res., 2002

Omnivergent Stereo.

Steven M. Seitz, Adam Kalai, Heung-Yeung Shum

Int. J. Comput. Vis., 2002

Efficient pattern-matching with don't cares.

Adam Kalai

Proceedings of the Thirteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2002

1999

Universal Portfolios With and Without Transaction Costs.

Avrim Blum, Adam Kalai

Mach. Learn., 1999

On-line algorithms for combining language models.

Adam Kalai, Stanley F. Chen, Avrim Blum, Ronald Rosenfeld

Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Finely-Competitive Paging.

Avrim Blum, Carl Burch, Adam Kalai

Proceedings of the 40th Annual Symposium on Foundations of Computer Science, 1999

Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation.

Avrim Blum, Adam Kalai, John Langford

Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998

A Note on Learning from Multiple-Instance Examples.

Avrim Blum, Adam Kalai

Mach. Learn., 1998