On the learnability of discrete distributions

Learning probabilistic automata with variable memory length

COLT '94 Proceedings of the seventh annual conference on Computational learning theory

On the learnability and usage of acyclic probabilistic finite automata

COLT '95 Proceedings of the eighth annual conference on Computational learning theory

On learning bounded-width branching programs

COLT '95 Proceedings of the eighth annual conference on Computational learning theory

Evaluation may be easier than generation (extended abstract)

STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing

Efficient algorithms for inverting evolution

STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing

Learning distributions from random walks

COLT '97 Proceedings of the tenth annual conference on Computational learning theory

Learning Markov chains with variable memory length from noisy output

COLT '97 Proceedings of the tenth annual conference on Computational learning theory

Property testing and its connection to learning and approximation

Journal of the ACM (JACM)

Estimating a mixture of two product distributions

COLT '99 Proceedings of the twelfth annual conference on Computational learning theory

Learning fixed-dimension linear thresholds from fragmented data

COLT '99 Proceedings of the twelfth annual conference on Computational learning theory

Efficient algorithms for inverting evolution

Journal of the ACM (JACM)

Mining specifications

POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages

Learning fixed-dimension linear thresholds from fragmented data

Information and Computation

Shallow Parsing Using Probabilistic Grammatical Inference

ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications

When Can Two Unsupervised Learners Achieve PAC Separation?

COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory

Boosting Density Function Estimators

ECML '02 Proceedings of the 13th European Conference on Machine Learning

PAC learning of probability distributions over a discrete domain

Theoretical Computer Science

Learning Mixtures of Gaussians

FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science

Part-of-speech tagging using a Variable Memory Markov model

ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics

PAC-learnability of Probabilistic Deterministic Finite State Automata

The Journal of Machine Learning Research

Learning nonsingular phylogenies and hidden Markov models

Proceedings of the thirty-seventh annual ACM symposium on Theory of computing

Probabilistic Finite-State Machines-Part II

IEEE Transactions on Pattern Analysis and Machine Intelligence

Probabilistic Finite-State Machines-Part I

IEEE Transactions on Pattern Analysis and Machine Intelligence

Code coverage testing using hardware performance monitoring support

Proceedings of the sixth international symposium on Automated analysis-driven debugging

Learning mixtures of product distributions over discrete domains

FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science

Streaming and sublinear approximation of entropy and information distances

SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm

Learning to impersonate

ICML '06 Proceedings of the 23rd international conference on Machine learning

Partially distribution-free learning of regular languages from positive samples

COLING '04 Proceedings of the 20th international conference on Computational Linguistics

Using Multiattribute Prediction Suffix Graphs to Predict and Generate Music

Computer Music Journal

XPathLearner: an on-line self-tuning Markov histogram for XML path selectivity estimation

VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases

PAC-learnability of probabilistic deterministic finite state automata in terms of variation distance

Theoretical Computer Science

Towards Feasible PAC-Learning of Probabilistic Deterministic Finite Automata

ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications

Markovian workload modeling for Enterprise Application Servers

C3S2E '09 Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering

Sublinear estimation of entropy and information distances

ACM Transactions on Algorithms (TALG)

Application of a generalization of russo's formula to learning from multiple random oracles

Combinatorics, Probability and Computing

A bibliographical study of grammatical inference

Pattern Recognition

Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms

Pattern Recognition

Natural language grammar induction with a generative constituent-context model

Pattern Recognition

Separating populations with wide data: a spectral analysis

ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation

Efficiently learning mixtures of two Gaussians

Proceedings of the forty-second ACM symposium on Theory of computing

A lower bound for learning distributions generated by probabilistic automata

ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory

Exact inference of hidden structure from sample data in noisy-OR networks

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence

Distribution rules with numeric attributes of interest

PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases

PAC-Learning of markov models with hidden state

ECML'06 Proceedings of the 17th European conference on Machine Learning

Private data release via learning thresholds

Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms

PAC-learnability of probabilistic deterministic finite state automata in terms of variation distance

ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory

Learnability of probabilistic automata via oracles

ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory

PAC learning axis-aligned mixtures of gaussians with no separation assumption

COLT'06 Proceedings of the 19th annual conference on Learning Theory

PAC-learning unambiguous NTS languages

ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications

Modeling sequences of user actions for statistical goal recognition

User Modeling and User-Adapted Interaction

Learning poisson binomial distributions

STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing

Characterizing pseudoentropy and simplifying pseudorandom generator constructions

STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing

On learning finite-state quantum sources

Quantum Information & Computation

A spectral algorithm for learning Hidden Markov Models

Journal of Computer and System Sciences

Learning probabilistic automata: A study in state distinguishability

Theoretical Computer Science

Learning mixtures of arbitrary distributions over large discrete domains

Proceedings of the 5th conference on Innovations in theoretical computer science

Automatic generation of compact formal properties for effective error detection

Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis