Adam Tauman Kalai

According to our database1, Adam Tauman Kalai authored at least 85 papers between 1998 and 2020.

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Bibliography

2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples.
CoRR, 2020

Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization.
CoRR, 2020

HAI-GEN 2020: Workshop on Human-AI Co-Creation with Generative Models.
Proceedings of the IUI '20: 25th International Conference on Intelligent User Interfaces, 2020

The disparate equilibria of algorithmic decision making when individuals invest rationally.
Proceedings of the FAT* '20: Conference on Fairness, 2020

2019
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes.
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.
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.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Learning to Prune: Speeding up Repeated Computations.
Proceedings of the Conference on Learning Theory, 2019

Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning.
Proceedings of the Algorithmic Learning Theory, 2019

What are the Biases in My Word Embedding?
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Algorithmic Greenlining: An Approach to Increase Diversity.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
When optimizing nonlinear objectives is no harder than linear objectives.
CoRR, 2018

Usability of Humanly Computable Passwords.
Proceedings of the Sixth AAAI Conference on Human Computation and Crowdsourcing, 2018

Decoupled Classifiers for Group-Fair and Efficient Machine Learning.
Proceedings of the Conference on Fairness, Accountability and Transparency, 2018

Actively Avoiding Nonsense in Generative Models.
Proceedings of the Conference On Learning Theory, 2018

Unleashing Linear Optimizers for Group-Fair Learning and Optimization.
Proceedings of the Conference On Learning Theory, 2018

Glass-Box Program Synthesis: A Machine Learning Approach.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Supervising Unsupervised Learning.
CoRR, 2017

Decoupled classifiers for fair and efficient machine learning.
CoRR, 2017

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

Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Counterfactual Language Model Adaptation for Suggesting Phrases.
Proceedings of the Eighth International Joint Conference on Natural Language Processing, 2017

Learning to Suggest Phrases.
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.
CoRR, 2016

Quantifying and Reducing Stereotypes in Word Embeddings.
CoRR, 2016

Reading and Learning Smartfonts.
Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 2016

On Suggesting Phrases vs. Predicting Words for Mobile Text Composition.
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.
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.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

OMG UR Funny! Computer-Aided Humor with an Application to Chat.
Proceedings of the Sixth International Conference on Computational Creativity, Park City, Utah, USA, June 29, 2015

Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons.
Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

2014
A Crowd of Your Own: Crowdsourcing for On-Demand Personalization.
Proceedings of the Seconf AAAI Conference on Human Computation and Crowdsourcing, 2014

2013
A colorful approach to text processing by example.
Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, 2013

Feature Multi-Selection among Subjective Features.
Proceedings of the 30th International Conference on Machine Learning, 2013

A Machine Learning Framework for Programming by Example.
Proceedings of the 30th International Conference on Machine Learning, 2013

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

2012
Reliable agnostic learning.
J. Comput. Syst. Sci., 2012

Textual Features for Programming by Example
CoRR, 2012

Disentangling Gaussians.
Commun. ACM, 2012

2011
Cooperation in two person games, revisited.
SIGecom Exch., 2011

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

Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression.
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.
Proceedings of the Innovations in Computer Science, 2011

Adaptively Learning the Crowd Kernel.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
A commitment folk theorem.
Games Econ. Behav., 2010

A Novel Approach to Propagating Distrust.
Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

Efficiently learning mixtures of two Gaussians.
Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

On the Equilibria of Alternating Move Games.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

Cooperation and competition in strategic games with private information.
Proceedings of the Proceedings 11th ACM Conference on Electronic Commerce (EC-2010), 2010

Tight asymptotic bounds for the deletion channel with small deletion probabilities.
Proceedings of the IEEE International Symposium on Information Theory, 2010

Playing Games without Observing Payoffs.
Proceedings of the Innovations in Computer Science, 2010

2009
Playing Games with Approximation Algorithms.
SIAM J. Comput., 2009

Analysis of Perceptron-Based Active Learning.
J. Mach. Learn. Res., 2009

Potential-Based Agnostic Boosting.
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.
Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science, 2009

The Isotron Algorithm: High-Dimensional Isotonic Regression.
Proceedings of the COLT 2009, 2009

2008
Agnostically Learning Halfspaces.
SIAM J. Comput., 2008

Decision trees are PAC-learnable from most product distributions: a smoothed analysis
CoRR, 2008

Trust-based recommendation systems: an axiomatic approach.
Proceedings of the 17th International Conference on World Wide Web, 2008

On agnostic boosting and parity learning.
Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Agnostically learning decision trees.
Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

A Query Algorithm for Agnostically Learning DNF?.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
The Myth of the Folk Theorem.
Electronic Colloquium on Computational Complexity (ECCC), 2007

Learning Nested Halfspaces and Uphill Decision Trees.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Simulated Annealing for Convex Optimization.
Math. Oper. Res., 2006

An Approach to Bounded Rationality.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Graph model selection using maximum likelihood.
Proceedings of the Machine Learning, 2006

Logarithmic Regret Algorithms for Online Convex Optimization.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
Efficient algorithms for online decision problems.
J. Comput. Syst. Sci., 2005

Boosting in the presence of noise.
J. Comput. Syst. Sci., 2005

Online convex optimization in the bandit setting: gradient descent without a gradient.
Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2005

From Batch to Transductive Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
Learning Monotonic Linear Functions.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
Generating Random Factored Numbers, Easily.
J. Cryptology, 2003

Noise-tolerant learning, the parity problem, and the statistical query model.
J. ACM, 2003

Admission Control to Minimize Rejections.
Internet Math., 2003

Static Optimality and Dynamic Search-Optimality in Lists and Trees.
Algorithmica, 2003

2002
Efficient Algorithms for Universal Portfolios.
J. Mach. Learn. Res., 2002

Omnivergent Stereo.
Int. J. Comput. Vis., 2002

Efficient pattern-matching with don't cares.
Proceedings of the Thirteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2002

1999
Universal Portfolios With and Without Transaction Costs.
Mach. Learn., 1999

On-line algorithms for combining language models.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Finely-Competitive Paging.
Proceedings of the 40th Annual Symposium on Foundations of Computer Science, 1999

Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
A Note on Learning from Multiple-Instance Examples.
Mach. Learn., 1998


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