Laws of large numbers and tail inequalities for random tries and PATRICIA trees
Journal of Computational and Applied Mathematics - Special issue: Probabilistic methods in combinatorics and combinatorial optimization
Model Selection and Error Estimation
Machine Learning
Random Structures & Algorithms - Probabilistic methods in combinatorial optimization
Mathematical Modelling of Generalization
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Data-Dependent Margin-Based Generalization Bounds for Classification
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Concentration for locally acting permutations
Discrete Mathematics
Machine learning with data dependent hypothesis classes
The Journal of Machine Learning Research
Data-dependent margin-based generalization bounds for classification
The Journal of Machine Learning Research
The Journal of Machine Learning Research
On the Independence Number of Random Interval Graphs
Combinatorics, Probability and Computing
Combinatorics, Probability and Computing
Generalization Error Bounds for Threshold Decision Lists
The Journal of Machine Learning Research
Expected worst-case partial match in random quadtries
Discrete Applied Mathematics - Brazilian symposium on graphs, algorithms and combinatorics
Oblivious routing in directed graphs with random demands
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
On the typical case complexity of graph optimization
Discrete Applied Mathematics - Special issue: Typical case complexity and phase transitions
Concentration for self-bounding functions and an inequality of Talagrand
Random Structures & Algorithms
Model selection by bootstrap penalization for classification
Machine Learning
Combining PAC-Bayesian and Generic Chaining Bounds
The Journal of Machine Learning Research
Aspects of discrete mathematics and probability in the theory of machine learning
Discrete Applied Mathematics
Efficient blocking probability computation of complex traffic flows for network dimensioning
Computers and Operations Research
Coding on countably infinite alphabets
IEEE Transactions on Information Theory
On the typical case complexity of graph optimization
Discrete Applied Mathematics
A discriminative model for semi-supervised learning
Journal of the ACM (JACM)
A constant factor approximation algorithm for generalized min-sum set cover
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Privately releasing conjunctions and the statistical query barrier
Proceedings of the forty-third annual ACM symposium on Theory of computing
The bounds on the rate of uniform convergence for learning machine
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
A PAC-Style model for learning from labeled and unlabeled data
COLT'05 Proceedings of the 18th annual conference on Learning Theory
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