Michael Kearns

Orcid: 0000-0001-7569-0147

Affiliations:
  • Department of Computer and Information Science, University of Pennsylvania


According to our database1, Michael Kearns authored at least 189 papers between 1987 and 2024.

Collaborative distances:
  • Dijkstra number2 of two.
  • Erdős number3 of three.

Awards

ACM Fellow

ACM Fellow 2014, "For contributions to machine learning, artificial intelligence, and algorithmic game theory and computational social science.".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable.
CoRR, 2024

Model Ensembling for Constrained Optimization.
CoRR, 2024

Oracle-Efficient Reinforcement Learning for Max Value Ensembles.
CoRR, 2024

Improved Differentially Private Regression via Gradient Boosting.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Membership Inference Attacks on Diffusion Models via Quantile Regression.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Balanced Filtering via Disclosure-Controlled Proxies.
Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

Diversified Ensembling: An Experiment in Crowdsourced Machine Learning.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023
Balanced Filtering via Non-Disclosive Proxies.
CoRR, 2023

AI Model Disgorgement: Methods and Choices.
CoRR, 2023

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

Scalable Membership Inference Attacks via Quantile Regression.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multicalibration as Boosting for Regression.
Proceedings of the International Conference on Machine Learning, 2023

Efficient Stackelberg Strategies for Finitely Repeated Games.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Multicalibrated Regression for Downstream Fairness.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
Confidence-Ranked Reconstruction of Census Microdata from Published Statistics.
CoRR, 2022

Beyond the Frontier: Fairness Without Accuracy Loss.
CoRR, 2022

Private Synthetic Data for Multitask Learning and Marginal Queries.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

An Algorithmic Framework for Bias Bounties.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Multiaccurate Proxies for Downstream Fairness.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Mixed Differential Privacy in Computer Vision.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Algorithms and Learning for Fair Portfolio Design.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Differentially Private Query Release Through Adaptive Projection.
Proceedings of the 38th International Conference on Machine Learning, 2021

Lexicographically Fair Learning: Algorithms and Generalization.
Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

An Algorithmic Framework for Fairness Elicitation.
Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

Minimax Group Fairness: Algorithms and Experiments.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020
Ethical algorithm design.
SIGecom Exch., 2020

Convergent Algorithms for (Relaxed) Minimax Fairness.
CoRR, 2020

Differentially Private Call Auctions and Market Impact.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Optimal, truthful, and private securities lending.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

2019
Competitive contagion in networks.
Games Econ. Behav., 2019

Eliciting and Enforcing Subjective Individual Fairness.
CoRR, 2019

Average Individual Fairness: Algorithms, Generalization and Experiments.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Equilibrium Characterization for Data Acquisition Games.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Network Formation under Random Attack and Probabilistic Spread.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Differentially Private Fair Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

An Empirical Study of Rich Subgroup Fairness for Machine Learning.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Fair Algorithms for Learning in Allocation Problems.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018
Online Learning with an Unknown Fairness Metric.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness.
Proceedings of the 35th International Conference on Machine Learning, 2018

Meritocratic Fairness for Infinite and Contextual Bandits.
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017
A Convex Framework for Fair Regression.
CoRR, 2017

Fair Algorithms for Machine Learning.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Fairness Incentives for Myopic Agents.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Meritocratic Fairness for Cross-Population Selection.
Proceedings of the 34th International Conference on Machine Learning, 2017

Fairness in Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Predicting with Distributions.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Private algorithms for the protected in social network search.
Proc. Natl. Acad. Sci. USA, 2016

Rawlsian Fairness for Machine Learning.
CoRR, 2016

Fair Learning in Markovian Environments.
CoRR, 2016

Mathematical foundations for social computing.
Commun. ACM, 2016

Strategic Network Formation with Attack and Immunization.
Proceedings of the Web and Internet Economics - 12th International Conference, 2016

Fairness in Learning: Classic and Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Tight Policy Regret Bounds for Improving and Decaying Bandits.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
Privacy for the Protected (Only).
CoRR, 2015

Robust Mediators in Large Games.
CoRR, 2015

Privacy and Truthful Equilibrium Selection for Aggregative Games.
Proceedings of the Web and Internet Economics - 11th International Conference, 2015

From "In" to "Over": Behavioral Experiments on Whole-Network Computation.
Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

Online Learning and Profit Maximization from Revealed Preferences.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
A Computational Study of Feasible Repackings in the FCC Incentive Auctions.
CoRR, 2014

Mechanism design in large games: incentives and privacy.
Proceedings of the Innovations in Theoretical Computer Science, 2014

Pursuit-Evasion Without Regret, with an Application to Trading.
Proceedings of the 31th International Conference on Machine Learning, 2014

Learning from Contagion (Without Timestamps).
Proceedings of the 31th International Conference on Machine Learning, 2014

Efficient Inference for Complex Queries on Complex Distributions.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

New Models for Competitive Contagion.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Nash Convergence of Gradient Dynamics in Iterated General-Sum Games
CoRR, 2013

Marginals-to-Models Reducibility.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Large-Scale Bandit Problems and KWIK Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

Depth-Workload Tradeoffs for Workforce Organization.
Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, 2013

2012
Experiments in social computation.
Commun. ACM, 2012

Colonel Blotto on Facebook: the effect of social relations on strategic interaction.
Proceedings of the Web Science 2012, 2012

Budget Optimization for Sponsored Search: Censored Learning in MDPs.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Competitive contagion in networks.
Proceedings of the 44th Symposium on Theory of Computing Conference, 2012

Behavioral experiments on a network formation game.
Proceedings of the 13th ACM Conference on Electronic Commerce, 2012

Experiments in social computation: (and the data they generate).
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Learning and predicting dynamic networked behavior with graphical multiagent models.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011
Bandits, Query Learning, and the Haystack Dimension.
Proceedings of the COLT 2011, 2011

Behavioral Conflict and Fairness in Social Networks.
Proceedings of the Internet and Network Economics - 7th International Workshop, 2011

Graphical Models for Bandit Problems.
Proceedings of the UAI 2011, 2011

Market making and mean reversion.
Proceedings of the Proceedings 12th ACM Conference on Electronic Commerce (EC-2011), 2011

A Clustering Coefficient Network Formation Game.
Proceedings of the Algorithmic Game Theory, 4th International Symposium, 2011

2010
Behavioral dynamics and influence in networked coloring and consensus.
Proc. Natl. Acad. Sci. USA, 2010

Censored exploration and the dark pool problem.
Commun. ACM, 2010

A behavioral study of bargaining in social networks.
Proceedings of the Proceedings 11th ACM Conference on Electronic Commerce (EC-2010), 2010

Local Algorithms for Finding Interesting Individuals in Large Networks.
Proceedings of the Innovations in Computer Science, 2010

Private and Third-Party Randomization in Risk-Sensitive Equilibrium Concepts.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Behavioral experiments on biased voting in networks.
Proc. Natl. Acad. Sci. USA, 2009

Network bargaining: algorithms and structural results.
Proceedings of the Proceedings 10th ACM Conference on Electronic Commerce (EC-2009), 2009

2008
Regret to the best vs. regret to the average.
Mach. Learn., 2008

Learning from Multiple Sources.
J. Mach. Learn. Res., 2008

Biased Voting and the Democratic Primary Problem.
Proceedings of the Internet and Network Economics, 4th International Workshop, 2008

Bargaining Solutions in a Social Network.
Proceedings of the Internet and Network Economics, 4th International Workshop, 2008

Behavioral experiments in networked trade.
Proceedings of the Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), 2008

Learning from Collective Behavior.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Empirical Price Modeling for Sponsored Search.
Proceedings of the Internet and Network Economics, Third International Workshop, 2007

Sponsored Search with Contexts.
Proceedings of the Internet and Network Economics, Third International Workshop, 2007

A network formation game for bipartite exchange economies.
Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2007

Privacy-Preserving Belief Propagation and Sampling.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Cobot in LambdaMOO: An Adaptive Social Statistics Agent.
Auton. Agents Multi Agent Syst., 2006

Networks preserving evolutionary equilibria and the power of randomization.
Proceedings of the Proceedings 7th ACM Conference on Electronic Commerce (EC-2006), 2006

(In)Stability properties of limit order dynamics.
Proceedings of the Proceedings 7th ACM Conference on Electronic Commerce (EC-2006), 2006

A Small World Threshold for Economic Network Formation.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Reinforcement learning for optimized trade execution.
Proceedings of the Machine Learning, 2006

Risk-Sensitive Online Learning.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005
Electronic Trading in Order-Driven Markets: Efficient Execution.
Proceedings of the 7th IEEE International Conference on E-Commerce Technology (CEC 2005), 2005

Learning from Data of Variable Quality.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Trading in Markovian Price Models.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004
Competitive algorithms for VWAP and limit order trading.
Proceedings of the Proceedings 5th ACM Conference on Electronic Commerce (EC-2004), 2004

Economic Properties of Social Networks.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

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

2003
The Penn-Lehman Automated Trading Project.
IEEE Intell. Syst., 2003

Structured interaction in game theory.
Proceedings of the 9th Conference on Theoretical Aspects of Rationality and Knowledge (TARK-2003), 2003

Correlated equilibria in graphical games.
Proceedings of the Proceedings 4th ACM Conference on Electronic Commerce (EC-2003), 2003

Algorithms for Interdependent Security Games.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Exploration in Metric State Spaces.
Proceedings of the Machine Learning, 2003

2002
Near-Optimal Reinforcement Learning in Polynomial Time.
Mach. Learn., 2002

A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes.
Mach. Learn., 2002

Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System.
J. Artif. Intell. Res., 2002

Efficient Nash Computation in Large Population Games with Bounded Influence.
Proceedings of the UAI '02, 2002

Nash Propagation for Loopy Graphical Games.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

A Note on the Representational Incompatibility of Function Approximation and Factored Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

CobotDS: A Spoken Dialogue System for Chat.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
ATTac-2000: An Adaptive Autonomous Bidding Agent.
J. Artif. Intell. Res., 2001

Graphical Models for Game Theory.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Cobot: A Social Reinforcement Learning Agent.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Computational Game Theory and AI.
Proceedings of the KI 2001: Advances in Artificial Intelligence, 2001

A social reinforcement learning agent.
Proceedings of the Fifth International Conference on Autonomous Agents, 2001

2000
Testing Problems with Sublearning Sample Complexity.
J. Comput. Syst. Sci., 2000

Nash Convergence of Gradient Dynamics in General-Sum Games.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Fast Planning in Stochastic Games.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

A Boosting Approach to Topic Spotting on Subdialogues.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Bias-Variance Error Bounds for Temporal Difference Updates.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

Automatic Optimization of Dialogue Management.
Proceedings of the COLING 2000, 18th International Conference on Computational Linguistics, Proceedings of the Conference, 2 Volumes, July 31, 2000

Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

Cobot in LambdaMOO: A Social Statistics Agent.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999
Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation.
Neural Comput., 1999

On the Boosting Ability of Top-Down Decision Tree Learning Algorithms.
J. Comput. Syst. Sci., 1999

Reinforcement Learning for Spoken Dialogue Systems.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Approximate Planning in Large POMDPs via Reusable Trajectories.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Efficient Reinforcement Learning in Factored MDPs.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Automatic Detection of Poor Speech Recognition at the Dialogue Level.
Proceedings of the 27th Annual Meeting of the Association for Computational Linguistics, 1999

1998
Efficient Noise-Tolerant Learning from Statistical Queries.
J. ACM, 1998

Large Deviation Methods for Approximate Probabilistic Inference.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Exact Inference of Hidden Structure from Sample Data in noisy-OR Networks.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Inference in Multilayer Networks via Large Deviation Bounds.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Near-Optimal Reinforcement Learning in Polynominal Time.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Theoretical Issues in Probabilistic Artificial Intelligence.
Proceedings of the 39th Annual Symposium on Foundations of Computer Science, 1998

Testing Problems with Sub-Learning Sample Complexity.
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering.
Proceedings of the Learning in Graphical Models, 1998

1997
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-test Split.
Neural Comput., 1997

An Experimental and Theoretical Comparison of Model Selection Methods.
Mach. Learn., 1997

Efficient Learning of Typical Finite Automata from Random Walks.
Inf. Comput., 1997

An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

1996
Rigorous Learning Curve Bounds from Statistical Mechanics.
Mach. Learn., 1996

Applying the Waek Learning Framework to Understand and Improve C4.5.
Proceedings of the Machine Learning, 1996

Boosting Theory Towards Practice: Recent Developments in Decision Tree Induction and the Weak Learning Framework.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995
On the Sample Complexity of Weakly Learning
Inf. Comput., March, 1995

Computational Learning Theory.
SIGACT News, 1995

Learning from a Population of Hypotheses.
Mach. Learn., 1995

On the Complexity of Teaching.
J. Comput. Syst. Sci., 1995

Horn Approximations of Empirical Data.
Artif. Intell., 1995

Efficient Algorithms for Learning to Play Repeated Games Against Computationally Bounded Adversaries.
Proceedings of the 36th Annual Symposium on Foundations of Computer Science, 1995

1994
Toward Efficient Agnostic Learning.
Mach. Learn., 1994

Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension.
Mach. Learn., 1994

Efficient Distribution-Free Learning of Probabilistic Concepts.
J. Comput. Syst. Sci., 1994

Cryptographic Limitations on Learning Boolean Formulae and Finite Automata.
J. ACM, 1994

Learning Boolean Formulas.
J. ACM, 1994

On the learnability of discrete distributions.
Proceedings of the Twenty-Sixth Annual ACM Symposium on Theory of Computing, 1994

Weakly learning DNF and characterizing statistical query learning using Fourier analysis.
Proceedings of the Twenty-Sixth Annual ACM Symposium on Theory of Computing, 1994

An Introduction to Computational Learning Theory.
MIT Press, ISBN: 978-0-262-11193-5, 1994

1993
Learning in the Presence of Malicious Errors.
SIAM J. Comput., 1993

Exact Identification of Read-Once Formulas Using Fixed Points of Amplification Functions.
SIAM J. Comput., 1993

Cryptographic Primitives Based on Hard Learning Problems.
Proceedings of the Advances in Cryptology, 1993

Reasoning With Characteristic Models.
Proceedings of the 11th National Conference on Artificial Intelligence. Washington, 1993

1992
Oblivious PAC Learning of Concept Hierarchies.
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

1991
Equivalence of Models for Polynomial Learnability
Inf. Comput., December, 1991

Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990
Efficient Distribution-free Learning of Probabilistic Concepts (Extended Abstract)
Proceedings of the 31st Annual Symposium on Foundations of Computer Science, 1990

Exact Identification of Circuits Using Fixed Points of Amplification Functions (Extended Abstract)
Proceedings of the 31st Annual Symposium on Foundations of Computer Science, 1990

Efficient Distribution-Free Learning of Probabilistic Concepts (Abstract).
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

Exact Identification of Circuits Using Fixed Points of Amplification Functions (Abstract).
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

On the Sample Complexity of Weak Learning.
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

Computational complexity of machine learning.
ACM distinguished dissertations, MIT Press, ISBN: 978-0-262-11152-2, 1990

1989
A General Lower Bound on the Number of Examples Needed for Learning
Inf. Comput., September, 1989

A Polynomial-Time Algorithm for Learning <i>k-</i>Variable Pattern Languages from Examples.
Proceedings of the Second Annual Workshop on Computational Learning Theory, 1989

1988
Learning in the Presence of Malicious Errors (Extended Abstract)
Proceedings of the 20th Annual ACM Symposium on Theory of Computing, 1988

1987
On the Learnability of Boolean Formulae
Proceedings of the 19th Annual ACM Symposium on Theory of Computing, 1987


  Loading...