Communications of the ACM
A new polynomial-time algorithm for linear programming
Combinatorica
How to construct random functions
Journal of the ACM (JACM)
Linear function neurons: Structure and training
Biological Cybernetics
On the learnability of Boolean formulae
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Information Processing Letters
Learning regular sets from queries and counterexamples
Information and Computation
Information and Computation
Automatic Pattern Recognition: A Study of the Probability of Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
Learning in the presence of malicious errors
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Computational limitations on learning from examples
Journal of the ACM (JACM)
Inferring decision trees using the minimum description length principle
Information and Computation
A general lower bound on the number of examples needed for learning
Information and Computation
Crytographic limitations on learning Boolean formulae and finite automata
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
What size net gives valid generalization?
Neural Computation
Training a 3-node neural network is NP-complete
COLT '88 Proceedings of the first annual workshop on Computational learning theory
Types of noise in data for concept learning
COLT '88 Proceedings of the first annual workshop on Computational learning theory
COLT '88 Proceedings of the first annual workshop on Computational learning theory
Some remarks about space-complexity of learning, and circuit complexity of recognizing
COLT '88 Proceedings of the first annual workshop on Computational learning theory
A parametrization scheme for classifying models of learnability
COLT '89 Proceedings of the second annual workshop on Computational learning theory
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
Linear Programming in Linear Time When the Dimension Is Fixed
Journal of the ACM (JACM)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Learning Conjunctive Concepts in Structural Domains
Machine Learning
Machine Learning
Machine Learning
Machine Learning
Machine Learning
ICALP '88 Proceedings of the 15th International Colloquium on Automata, Languages and Programming
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
Probabilistic inductive inference
Journal of the ACM (JACM)
Learnable and Nonlearnable Visual Concepts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some new bounds for Epsilon-nets
SCG '90 Proceedings of the sixth annual symposium on Computational geometry
How to net a lot with little: small &egr;-nets for disks and halfspaces
SCG '90 Proceedings of the sixth annual symposium on Computational geometry
On the necessity of Occam algorithms
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Approximations and optimal geometric divide-and-conquer
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
Semantic complexity of classes of relational queries and query independent data partitioning
PODS '91 Proceedings of the tenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Learning the Fourier spectrum of probabilistic lists and trees
SODA '91 Proceedings of the second annual ACM-SIAM symposium on Discrete algorithms
Computational learning theory: survey and selected bibliography
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Learning with a slowly changing distribution
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Polynomial uniform convergence and polynomial-sample learnability
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Learning stochastic functions by smooth simultaneous estimation
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
On exact specification by examples
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Characterizations of learnability for classes of {O, …, n}-valued functions
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Toward efficient agnostic learning
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
PAB-decisions for Boolean and real-valued features
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Robust trainability of single neurons
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Efficient noise-tolerant learning from statistical queries
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Learning sparse multivariate polynomials over a field with queries and counterexamples
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Lower bounds on the Vapnik-Chervonenkis dimension of multi-layer threshold networks
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On the power of polynomial discriminators and radial basis function networks
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On learning in the limit and non-uniform (&egr;,&dgr;)-learning
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On-line learning of rectangles in noisy environments
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Localization vs. identification of semi-algebraic sets
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Bounding the Vapnik-Chervonenkis dimension of concept classes parameterized by real numbers
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Conservativeness and monotonicity for learning algorithms
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Lower bounds for PAC learning with queries
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
General bounds on the number of examples needed for learning probabilistic concepts
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Hybrid pattern recognition system capable of self-modification
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Theory and Practice of Vector Quantizers Trained on Small Training Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
Almost optimal set covers in finite VC-dimension: (preliminary version)
SCG '94 Proceedings of the tenth annual symposium on Computational geometry
On the limits of proper learnability of subclasses of DNF formulas
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
The minimum L-complexity algorithm and its applications to learning non-parametric rules
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning unions of boxes with membership and equivalence queries
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Geometrical concept learning and convex polytopes
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning one-dimensional geometric patterns under one-sided random misclassification noise
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Fat-shattering and the learnability of real-valued functions
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning from a consistently ignorant teacher
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Lower bounds on the VC-dimension of smoothly parametrized function classes
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Efficient distribution-free learning of probabilistic concepts
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
Journal of Computer and System Sciences
1994 Special Issue: Design and evolution of modular neural network architectures
Neural Networks - Special issue: models of neurodynamics and behavior
Weakly learning DNF and characterizing statistical query learning using Fourier analysis
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Simulating access to hidden information while learning
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
On the learnability of discrete distributions
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
How many queries are needed to learn?
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Additive versus exponentiated gradient updates for linear prediction
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
On real Turing machines that toss coins
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
On randomized one-round communication complexity
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Reducing the number of queries in self-directed learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Being taught can be faster than asking questions
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
From noise-free to noise-tolerant and from on-line to batch learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Sample sizes for sigmoidal neural networks
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant parallel learning of geometric concepts
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
On efficient agnostic learning of linear combinations of basis functions
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
More theorems about scale-sensitive dimensions and learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Learning from a mixture of labeled and unlabeled examples with parametric side information
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Specification and simulation of statistical query algorithms for efficiency and noise tolerance
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
A note on VC-dimension and measures of sets of reals
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Optimal prefetching via data compression
Journal of the ACM (JACM)
How many queries are needed to learn?
Journal of the ACM (JACM)
Noise-tolerant learning near the information-theoretic bound
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Noise-tolerant distribution-free learning of general geometric concepts
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
VC dimension of an integrate-and-fire neuron model
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
PAC-like upper bounds for the sample complexity of leave-one-out cross-validation
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
On the complexity of learning from drifting distributions
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Learning changing concepts by exploiting the structure of change
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
PAC learning intersections of halfspaces with membership queries (extended abstract)
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Strong minimax lower bounds for learning
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Journal of the ACM (JACM)
Approximating hyper-rectangles: learning and pseudo-random sets
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Scale-sensitive dimensions, uniform convergence, and learnability
Journal of the ACM (JACM)
On the complexity of learning for a spiking neuron (extended abstract)
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Computational sample complexity
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Dense shattering and teaching dimensions for differentiable families (extended abstract)
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
A new composition theorem for learning algorithms
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Improved lower bounds for learning from noisy examples: an information-theoretic approach
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
The complexity of learning according to two models of a drifting environment
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
On the sample complexity of learning functions with bounded variation
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Cross-validation for binary classification by real-valued functions: theoretical analysis
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Property testing and its connection to learning and approximation
Journal of the ACM (JACM)
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Strong Minimax Lower Bounds for Learning
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Hardness Results for Learning First-Order Representations and Programming by Demonstration
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
On Restricted-Focus-of-Attention Learnability of Boolean Functions
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Identification criteria and lower bounds for perceptron-like learning rules
Neural Computation
Noise-tolerant distribution-free learning of general geometric concepts
Journal of the ACM (JACM)
Efficient noise-tolerant learning from statistical queries
Journal of the ACM (JACM)
On the effect of analog noise in discrete-time analog computations
Neural Computation
Localization vs. Identification of Semi-Algebraic Sets
Machine Learning
Prioritizing Information for the Discovery of Phenomena
Journal of Intelligent Information Systems
Exact and approximate aggregation in constraint query languages
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
An apprentice learning model (extended abstract)
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
On PAC learning using Winnow, Perceptron, and a Perceptron-like algorithm
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
VC-Dimension Analysis of Object Recognition Tasks
Journal of Mathematical Imaging and Vision
Efficient exploration for optimizing immediate reward
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Sample-efficient strategies for learning in the presence of noise
Journal of the ACM (JACM)
Learning Function-Free Horn Expressions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
The Complexity of Learning According to Two Models of a Drifting Environment
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
On the Sample Complexity for Nonoverlapping Neural Networks
Machine Learning
Multiple Comparisons in Induction Algorithms
Machine Learning
How Bad May Learning Curves Be?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Knowledge Incorporation into Neural Networks From Fuzzy Rules
Neural Processing Letters
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Learning and decision-making in the framework of fuzzy lattices
New learning paradigms in soft computing
New learning paradigms in soft computing
Learning fixed-dimension linear thresholds from fragmented data
Information and Computation
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Model complexity control and statisticallearning theory
Natural Computing: an international journal
Transfer theorems via sign conditions
Information Processing Letters
Efficient distribution-free population learning of simple concepts
Annals of Mathematics and Artificial Intelligence
Open Systems & Information Dynamics
Probabilistic ’generalization‘ of functions and dimension-based uniform convergence results
Statistics and Computing
Learning Changing Concepts by Exploiting the Structure of Change
Machine Learning
Stochastic Finite Learning of the Pattern Languages
Machine Learning
PAC Analogues of Perceptron and Winnow Via Boosting the Margin
Machine Learning
A perspective view and survey of meta-learning
Artificial Intelligence Review
Estimates of average complexity of neurocontrol algorithms
Neural Networks
Theoretical Computer Science
On computing the diameter of a point set in high dimensional Euclidean space
Theoretical Computer Science
IEEE Transactions on Knowledge and Data Engineering
R-MINI: An Iterative Approach for Generating Minimal Rules from Examples
IEEE Transactions on Knowledge and Data Engineering
Use of Contextual Information for Feature Ranking and Discretization
IEEE Transactions on Knowledge and Data Engineering
Knowledge Discovery by Inductive Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Algorithms for Finding Attribute Value Group for Binary Segmentation of Categorical Databases
IEEE Transactions on Knowledge and Data Engineering
On Learning to Recognize 3-D Objects from Examples
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Separations by Boolean Combinations of Half-Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occam Algorithms for Computing Visual Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Expert Network for DNA Sequence Analysis
IEEE Intelligent Systems
A linear lower bound on the unbounded error probabilistic communication complexity
Journal of Computer and System Sciences - Complexity 2001
Neural networks with local receptive fields and superlinear VC Dimension
Neural Computation
Training a single sigmoidal neuron is hard
Neural Computation
Information Processing Letters
Boosting and Hard-Core Set Construction
Machine Learning
On the Learnability of Hidden Markov Models
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
GA-Based Learning of kDNFns Boolean Formulas
ICES '01 Proceedings of the 4th International Conference on Evolvable Systems: From Biology to Hardware
SAGA '01 Proceedings of the International Symposium on Stochastic Algorithms: Foundations and Applications
Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Mathematical Modelling of Generalization
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Structural Complexity and Neural Networks
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Approximations by OBDDs and the Variable Ordering Problem
ICAL '99 Proceedings of the 26th International Colloquium on Automata, Languages and Programming
Sample Complexity for Function Learning Tasks through Linear Neural Networks
MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Reduced Support Vector Selection by Linear Programs
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Learnability and Definability in Trees and Similar Structures
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
Learning from Approximate Data
COCOON '00 Proceedings of the 6th Annual International Conference on Computing and Combinatorics
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Some Prospects for Efficient Fixed Parameter Algorithms
SOFSEM '98 Proceedings of the 25th Conference on Current Trends in Theory and Practice of Informatics: Theory and Practice of Informatics
Coherent Concepts, Robust Learning
SOFSEM '99 Proceedings of the 26th Conference on Current Trends in Theory and Practice of Informatics on Theory and Practice of Informatics
On the Sample Complexity for Neural Trees
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Learning Real Polynomials with a Turing Machine
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
The VC-Dimension of Subclasses of Pattern
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Learning Intermediate Concepts
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
Minimizing the Quadratic Training Error of a Sigmoid Neuron Is Hard
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
Extending Elementary Formal Systems
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
On Learning Embedded Midbit Functions
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
A General Dimension for Approximately Learning Boolean Functions
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Solving Computational Learning Problems of Boolean Formulae on DNA Computers
DNA '00 Revised Papers from the 6th International Workshop on DNA-Based Computers: DNA Computing
The Consistency Dimension, Compactness, and Query Learning
CSL '99 Proceedings of the 13th International Workshop and 8th Annual Conference of the EACSL on Computer Science Logic
On Agnostic Learning with {0, *, 1}-Valued and Real-Valued Hypotheses
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
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
Using the Pseudo-Dimension to Analyze Approximation Algorithms for Integer Programming
WADS '01 Proceedings of the 7th International Workshop on Algorithms and Data Structures
Query-preserving watermarking of relational databases and XML documents
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Advanced elementary formal systems
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
A theoretical framework for learning from a pool of disparate data sources
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning from rounded-off data
Information and Computation
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
On the difficulty of approximately maximizing agreements
Journal of Computer and System Sciences
DNA-based algorithms for learning Boolean formulae
Natural Computing: an international journal
Definable relations and first-order query languages over strings
Journal of the ACM (JACM)
On learning multicategory classification with sample queries
Information and Computation
Information Processing Letters
The Journal of Machine Learning Research
Optimally-smooth adaptive boosting and application to agnostic learning
The Journal of Machine Learning Research
On the proper learning of axis-parallel concepts
The Journal of Machine Learning Research
Optimized Disjunctive Association Rules via Sampling
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
The monotone theory for the PAC-model
Information and Computation
Intrinsic complexity of learning geometrical concepts from positive data
Journal of Computer and System Sciences
Functional Validation in Grid Computing
Autonomous Agents and Multi-Agent Systems
Efficient algorithms for learning functions with bounded variation
Information and Computation
A Note on VC-Dimension and Measure of Sets of Reals
Combinatorics, Probability and Computing
Function Learning from Interpolation
Combinatorics, Probability and Computing
Theoretical Computer Science - Special issue: Algorithmic learning theory
Network failure detection and graph connectivity
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Journal of Computer and System Sciences - STOC 2001
Generalization Error Bounds for Threshold Decision Lists
The Journal of Machine Learning Research
Learning intersections and thresholds of halfspaces
Journal of Computer and System Sciences - Special issue on FOCS 2002
Version spaces and the consistency problem
Artificial Intelligence
Some Dichotomy Theorems for Neural Learning Problems
The Journal of Machine Learning Research
On data classification by iterative linear partitioning
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
Some connections between learning and optimization
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees
The Journal of Machine Learning Research
Relevant Data Expansion for Learning Concept Drift from Sparsely Labeled Data
IEEE Transactions on Knowledge and Data Engineering
Hitting sets when the VC-dimension is small
Information Processing Letters
On the influence of the variable ordering for algorithmic learning using OBDDs
Information and Computation
On the Nonlearnability of a Single Spiking Neuron
Neural Computation
Finding small balanced separators
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
On learning embedded midbit functions
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Maximizing agreements and coagnostic learning
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Polynomial certificates for propositional classes
Information and Computation
Complexity parameters for first order classes
Machine Learning
The VC dimension of k-fold union
Information Processing Letters
On ordinal VC-dimension and some notions of complexity
Theoretical Computer Science - Algorithmic learning theory
From learning in the limit to stochastic finite learning
Theoretical Computer Science - Algorithmic learning theory
A new PAC bound for intersection-closed concept classes
Machine Learning
Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation
International Journal of Approximate Reasoning
On the generalization error of fixed combinations of classifiers
Journal of Computer and System Sciences
Pattern Recognition for Conditionally Independent Data
The Journal of Machine Learning Research
A bound on the label complexity of agnostic active learning
Proceedings of the 24th international conference on Machine learning
Learning intersections of halfspaces with a margin
Journal of Computer and System Sciences
Catching elephants with mice: sparse sampling for monitoring sensor networks
Proceedings of the 5th international conference on Embedded networked sensor systems
Aspects of discrete mathematics and probability in the theory of machine learning
Discrete Applied Mathematics
Neural Computation
The lack of a priori distinctions between learning algorithms
Neural Computation
Vc dimension of an integrate-and-fire neuron model
Neural Computation
On learning perceptrons with binary weights
Neural Computation
Vapnik-chervonenkis dimension bounds for two-and three-layer networks
Neural Computation
The value of agreement a new boosting algorithm
Journal of Computer and System Sciences
On hardness of learning intersection of two halfspaces
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
VC Dimension Bounds for Analytic Algebraic Computations
COCOON '08 Proceedings of the 14th annual international conference on Computing and Combinatorics
Hashed samples: selectivity estimators for set similarity selection queries
Proceedings of the VLDB Endowment
Reducing mechanism design to algorithm design via machine learning
Journal of Computer and System Sciences
Journal of the ACM (JACM)
Shifting: One-inclusion mistake bounds and sample compression
Journal of Computer and System Sciences
Using a similarity measure for credible classification
Discrete Applied Mathematics
The complexity of ranking hypotheses in optimality theory
Computational Linguistics
Small-size ε-nets for axis-parallel rectangles and boxes
Proceedings of the forty-first annual ACM symposium on Theory of computing
Using the doubling dimension to analyze the generalization of learning algorithms
Journal of Computer and System Sciences
New bounds on classical and quantum one-way communication complexity
Theoretical Computer Science
Learning Halfspaces with Malicious Noise
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Baum's Algorithm Learns Intersections of Halfspaces with Respect to Log-Concave Distributions
APPROX '09 / RANDOM '09 Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
A theory of expressiveness in mechanisms
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
A model of inductive bias learning
Journal of Artificial Intelligence Research
A formal framework for speedup learning from problems and solutions
Journal of Artificial Intelligence Research
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Inductive learning from good examples
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Curse of Dimensionality in Pivot Based Indexes
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
k-Fold unions of low-dimensional concept classes
Information Processing Letters
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The complexity of theory revision
Artificial Intelligence
Maximal width learning of binary functions
Theoretical Computer Science
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Hierarchical cooperation in ad hoc networks: optimal clustering and achievable throughput
IEEE Transactions on Information Theory
On data classification by iterative linear partitioning
Discrete Applied Mathematics
Some connections between learning and optimization
Discrete Applied Mathematics
A discriminative model for semi-supervised learning
Journal of the ACM (JACM)
Splice site prediction using support vector machines with a Bayes kernel
Expert Systems with Applications: An International Journal
On the influence of the variable ordering for algorithmic learning using OBDDs
Information and Computation
Polynomial certificates for propositional classes
Information and Computation
Hitting sets when the VC-dimension is small
Information Processing Letters
An experimental analysis of the impact of accuracy degradation in SVM classification
International Journal of Computational Intelligence Studies
Neural network architecture selection: can function complexity help?
Neural Processing Letters
Application of a generalization of russo's formula to learning from multiple random oracles
Combinatorics, Probability and Computing
Annals of Mathematics and Artificial Intelligence
Learning Halfspaces with Malicious Noise
The Journal of Machine Learning Research
Playing monotone games to understand learning behaviors
Theoretical Computer Science
TTCN-3 quality engineering: using learning techniques to evaluate metric sets
SDL'07 Proceedings of the 13th international SDL Forum conference on Design for dependable systems
Partial observability and learnability
Artificial Intelligence
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
On the Foundations of Noise-free Selective Classification
The Journal of Machine Learning Research
Probably approximately correct learning
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Learning with many irrelevant features
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Oblivious PAC learning of concept hierarchies
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Version spaces without boundary sets
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Universal ε-approximators for integrals
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Algorithms and theory of computation handbook
On the hardness of learning intersections of two halfspaces
Journal of Computer and System Sciences
PAC learnability of a concept class under non-atomic measures: a problem by Vidyasagar
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
An improved lower bound on query complexity for quantum PAC learning
Information Processing Letters
Query-preserving watermarking of relational databases and Xml documents
ACM Transactions on Database Systems (TODS)
Learnability, Stability and Uniform Convergence
The Journal of Machine Learning Research
Small-Size $\eps$-Nets for Axis-Parallel Rectangles and Boxes
SIAM Journal on Computing
Theoretical Computer Science
Determination and the no-free-lunch paradox
Neural Computation
Formal and empirical grammatical inference
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts of ACL 2011
Automatically building training examples for entity extraction
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Synthesis of optimal switching logic for hybrid systems
EMSOFT '11 Proceedings of the ninth ACM international conference on Embedded software
Supervised learning and co-training
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Assessing test adequacy for black-box systems without specifications
ICTSS'11 Proceedings of the 23rd IFIP WG 6.1 international conference on Testing software and systems
On exact learning halfspaces with random consistent hypothesis oracle
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Learning-Related complexity of linear ranking functions
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Data reduction for weighted and outlier-resistant clustering
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Functional classification with margin conditions
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Robust cutpoints in the logical analysis of numerical data
Discrete Applied Mathematics
On PAC learning algorithms for rich boolean function classes
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Bounds on the sample complexity for private learning and private data release
TCC'10 Proceedings of the 7th international conference on Theory of Cryptography
Learnability of bipartite ranking functions
COLT'05 Proceedings of the 18th annual conference on Learning Theory
The value of agreement, a new boosting algorithm
COLT'05 Proceedings of the 18th annual conference on Learning Theory
A PAC-Style model for learning from labeled and unlabeled data
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Estimation of a data-collection maturity model to detect manufacturing change
Expert Systems with Applications: An International Journal
The lixto project: exploring new frontiers of web data extraction
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
Time complexity of decision trees
Transactions on Rough Sets III
Active learning via perfect selective classification
The Journal of Machine Learning Research
Generalization error bounds for the logical analysis of data
Discrete Applied Mathematics
Artificial Intelligence in Medicine
Generalization capability of artificial neural network incorporated with pruning method
ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security
An approach to guided learning of boolean functions
Mathematical and Computer Modelling: An International Journal
Cognitive Systems Research
A geometric approach to sample compression
The Journal of Machine Learning Research
Activized learning: transforming passive to active with improved label complexity
The Journal of Machine Learning Research
LEARNING AND VERIFYING SAFETY CONSTRAINTS FOR PLANNERS IN A KNOWLEDGE-IMPOVERISHED SYSTEM
Computational Intelligence
Analysis of a multi-category classifier
Discrete Applied Mathematics
PAC learnability of rough hypercuboid classifier
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Learning in the limit with lattice-structured hypothesis spaces
Theoretical Computer Science
Maximal pattern complexity, dual system and pattern recognition
Theoretical Computer Science
Unimprovable Upper Bounds on Time Complexity of Decision Trees
Fundamenta Informaticae
ON A QUANTITATIVE NOTION OF UNIFORMITY
Fundamenta Informaticae
MFCS'07 Proceedings of the 32nd international conference on Mathematical Foundations of Computer Science
Fast vertex guarding for polygons with and without holes
Computational Geometry: Theory and Applications
Characterizing the sample complexity of private learners
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
PAC learnability under non-atomic measures: A problem by Vidyasagar
Theoretical Computer Science
Exploiting label dependencies for improved sample complexity
Machine Learning
Bias-variance tradeoffs in program analysis
Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages
Uniform convergence, stability and learnability for ranking problems
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Unsolved problems in visibility graphs of points, segments, and polygons
ACM Computing Surveys (CSUR)
An efficient construction and application usefulness of rectangle greedy covers
Pattern Recognition
Supervised learning and Co-training
Theoretical Computer Science
Algorithms and hardness results for parallel large margin learning
The Journal of Machine Learning Research
Learning bounds via sample width for classifiers on finite metric spaces
Theoretical Computer Science
| Hi-index | 0.08 |
Valiant's learnability model is extended to learning classes of concepts defined by regions in Euclidean space En. The methods in this paper lead to a unified treatment of some of Valiant's results, along with previous results on distribution-free convergence of certain pattern recognition algorithms. It is shown that the essential condition for distribution-free learnability is finiteness of the Vapnik-Chervonenkis dimension, a simple combinatorial parameter of the class of concepts to be learned. Using this parameter, the complexity and closure properties of learnable classes are analyzed, and the necessary and sufficient conditions are provided for feasible learnability.