Toward efficient agnostic learning
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Finiteness results for sigmoidal “neural” networks
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Bounds for the computational power and learning complexity of analog neural nets
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
Learning from a population of hypotheses
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Learning with restricted focus of attention
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On-line learning of functions of bounded variation under various sampling schemes
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Efficient agnostic PAC-learning with simple hypothesis
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Rigorous learning curve bounds from statistical mechanics
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
An optimal-control application of two paradigms of on-line learning
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
Fat-shattering and the learnability of real-valued functions
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Efficient learning of continuous neural networks
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
On the learnability of discrete distributions
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Polynomial bounds for VC dimension of sigmoidal neural networks
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
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
Learning internal representations
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Concept learning with geometric hypotheses
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
More or less efficient agnostic learning of convex polygons
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
More theorems about scale-sensitive dimensions and learning
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
Towards robust model selection using estimation and approximation error bounds
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
The importance of convexity in learning with squared loss
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Analysis of greedy expert hiring and an application to memory-based learning (extended abstract)
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Learning of depth two neural networks with constant fan-in at the hidden nodes (extended abstract)
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Noise injection: theoretical prospects
Neural Computation
The Racing Algorithm: Model Selection for Lazy Learners
Artificial Intelligence Review - Special issue on lazy 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
Performance bounds for nonlinear time series prediction
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Learning distributions from random walks
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Agnostic learning of geometric patterns (extended abstract)
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
The Sample Complexity of Learning Fixed-Structure Bayesian Networks
Machine Learning - Special issue on learning with probabilistic representations
Improved boosting algorithms using confidence-rated predictions
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
Sample complexity of model-based search
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Function Estimation by Feedforward Sigmoidal Networks with BoundedWeights
Neural Processing Letters
On the effect of analog noise in discrete-time analog computations
Neural Computation
Prequential and Cross-Validated Regression Estimation
Machine Learning
Learning fixed-dimension linear thresholds from fragmented data
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
Estimation of Time-Varying Parameters in Statistical Models: AnOptimization Approach
Machine Learning - Special issue: computational learning theory, COLT '97
Improved Boosting Algorithms Using Confidence-rated Predictions
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
Improved bounds on the sample complexity of learning
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
On the Sample Complexity for Nonoverlapping Neural Networks
Machine Learning
Spatial Color Indexing and Applications
International Journal of Computer Vision
Nonparametric Time Series Prediction Through Adaptive ModelSelection
Machine Learning
Sublinear time approximate clustering
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
A comparison of identification criteria for inductive inference of recursive real-valued functions
Theoretical Computer Science - Algorithmic learning theory
Learning fixed-dimension linear thresholds from fragmented data
Information and Computation
Prediction from randomly right censored data
Journal of Multivariate Analysis
Probabilistic ’generalization‘ of functions and dimension-based uniform convergence results
Statistics and Computing
Learning Changing Concepts by Exploiting the Structure of Change
Machine Learning
A Guide to the Literature on Learning Probabilistic Networks from Data
IEEE Transactions on Knowledge and Data Engineering
PAC Learning with Generalized Samples and an Applicaiton to Stochastic Geometry
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hardness results for neural network approximation problems
Theoretical Computer Science
Learning cost-sensitive active classifiers
Artificial Intelligence
Neural networks with local receptive fields and superlinear VC Dimension
Neural Computation
Learning to recognize three-dimensional objects
Neural Computation
A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
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
On the Generalization Ability of Recurrent Networks
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Hardness Results for Neural Network Approximation Problems
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
On the Sample Complexity for Neural Trees
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
A Comparison of Identification Criteria for Inductive Inference of Recursive Real-Valued Functions
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases
ALT '98 Proceedings of the 9th 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
Average-Case Analysis of Classification Algorithms for Boolean Functions and Decision Trees
ALT '00 Proceedings of the 11th International Conference on Algorithmic Learning Theory
An Efficient PAC Algorithm for Reconstructing a Mixture of Lines
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Maximizing Agreements and CoAgnostic Learning
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Practical Algorithms for On-line Sampling
DS '98 Proceedings of the First International Conference on Discovery Science
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
Bounds on Sample Size for Policy Evaluation in Markov Environments
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Bounds for the Minimum Disagreement Problem with Applications to Learning Theory
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Agnostic Learning Nonconvex Function Classes
COLT '02 Proceedings of the 15th Annual 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
Optimal indexing using near-minimal space
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Machine Learning
Multiple-Instance Learning of Real-Valued Geometric Patterns
Annals of Mathematics and Artificial Intelligence
On the difficulty of approximately maximizing agreements
Journal of Computer and System Sciences
An introduction to boosting and leveraging
Advanced lectures on machine learning
On learning multicategory classification with sample queries
Information and Computation
Algorithms column: sublinear time algorithms
ACM SIGACT News
Comparing Bayes model averaging and stacking when model approximation error cannot be ignored
The Journal of Machine Learning Research
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Efficient algorithms for learning functions with bounded variation
Information and Computation
Function Learning from Interpolation
Combinatorics, Probability and Computing
Information Fusion Methods Based on Physical Laws
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some connections between learning and optimization
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
On k-Median clustering in high dimensions
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Learning in natural language: theory and algorithmic approaches
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
The VC Dimension for Mixtures of Binary Classifiers
Neural Computation
Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks
Neural Computation
Maximizing agreements and coagnostic learning
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Estimating relatedness via data compression
ICML '06 Proceedings of the 23rd international conference on Machine learning
Theoretical Computer Science - Computing and combinatorics
A Nonparametric Approach to Multiproduct Pricing
Operations Research
A PTAS for k-means clustering based on weak coresets
SCG '07 Proceedings of the twenty-third annual symposium on Computational geometry
On approximate halfspace range counting and relative epsilon-approximations
SCG '07 Proceedings of the twenty-third annual symposium on Computational geometry
A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians
The Journal of Machine Learning Research
The VC dimension of k-uniform random hypergraphs
Random Structures & Algorithms
A bound on the label complexity of agnostic active learning
Proceedings of the 24th international conference on Machine learning
Aspects of discrete mathematics and probability in the theory of machine learning
Discrete Applied Mathematics
Incentive compatible regression learning
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Vapnik-chervonenkis generalization bounds for real valued neural networks
Neural Computation
Nonlinear Function Learning Using Radial Basis Function Networks: Convergence and Rates
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Learning from Multiple Sources
The Journal of Machine Learning Research
Coresets and approximate clustering for Bregman divergences
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
A model of inductive bias learning
Journal of Artificial Intelligence Research
Convergence of reinforcement learning with general function approximators
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Learning with annotation noise
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Achievability results for statistical learning under communication constraints
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
Some connections between learning and optimization
Discrete Applied Mathematics
Teaching dimension and the complexity of active learning
COLT'07 Proceedings of the 20th annual conference on Learning theory
Approximation with neural networks activated by ramp sigmoids
Journal of Approximation Theory
Simulation-based optimization of Markov decision processes: An empirical process theory approach
Automatica (Journal of IFAC)
Incentive compatible regression learning
Journal of Computer and System Sciences
Probably approximately correct learning
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
A new metric-based approach to model selection
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Algorithms and theory of computation handbook
The classification game: complexity regularization through interaction
COIN'09 Proceedings of the 5th international conference on Coordination, organizations, institutions, and norms in agent systems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Optimal adaptive sampling recovery
Advances in Computational Mathematics
Learnability, Stability and Uniform Convergence
The Journal of Machine Learning Research
Approximate Halfspace Range Counting
SIAM Journal on Computing
PEGASUS: a policy search method for large MDPs and POMDPs
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Efficient Learning with Partially Observed Attributes
The Journal of Machine Learning Research
SIAM Journal on Computing
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Learning hurdles for sleeping experts
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Hardness results for agnostically learning low-degree polynomial threshold functions
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Learnability of bipartite ranking functions
COLT'05 Proceedings of the 18th annual conference on Learning Theory
A simple feature extraction for high dimensional image representations
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Randomized algorithms for robust controller synthesis using statistical learning theory
Automatica (Journal of IFAC)
Brief Finite sample properties of system identification of ARX models under mixing conditions
Automatica (Journal of IFAC)
Journal of Computer and System Sciences
A complete characterization of statistical query learning with applications to evolvability
Journal of Computer and System Sciences
Learning with stochastic inputs and adversarial outputs
Journal of Computer and System Sciences
Activized learning: transforming passive to active with improved label complexity
The Journal of Machine Learning Research
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
Automatic Programming of Morphological Machines by PAC Learning
Fundamenta Informaticae
An invariance principle for polytopes
Journal of the ACM (JACM)
PAC-Learning with general class noise models
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
Approximation and estimation bounds for free knot splines
Computers & Mathematics with Applications
Small-size relative (p,ε)-approximations for well-behaved range spaces
Proceedings of the twenty-ninth annual symposium on Computational geometry
Learning Big (Image) Data via Coresets for Dictionaries
Journal of Mathematical Imaging and Vision
Universal learning using free multivariate splines
Neurocomputing
Generalization ability of fractional polynomial models
Neural Networks
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