Pages that link to "Item:Q1198550"

The following pages link to Decision theoretic generalizations of the PAC model for neural net and other learning applications (Q1198550):

Displaying 40 items.

• Theory of Classification: a Survey of Some Recent Advances (Q3373749) (← links)
• Amplification of One-Way Information Complexity via Codes and Noise Sensitivity (Q3448852) (← links)
• Sample Complexity Bounds on Differentially Private Learning via Communication Complexity (Q3454521) (← links)
• Reconstructing Algebraic Functions from Mixed Data (Q4210162) (← links)
• Neural Networks with Local Receptive Fields and Superlinear VC Dimension (Q4330677) (← links)
• ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY (Q4474578) (← links)
• Learning to Recognize Three-Dimensional Objects (Q4542439) (← links)
• Non-parametric regression for spatially dependent data with wavelets (Q4559353) (← links)
• Submodular Functions: Learnability, Structure, and Optimization (Q4564777) (← links)
• (Q4614114) (← links)
• Robust Estimators in High-Dimensions Without the Computational Intractability (Q4634036) (← links)
• Valid Generalisation from Approximate Interpolation (Q4715266) (← links)
• Recurrent Neural Networks with Small Weights Implement Definite Memory Machines (Q4814203) (← links)
• Metric Entropy for Functions of Bounded Total Generalized Variation (Q4964802) (← links)
• Neural networks and some applications to finance (Q4994396) (← links)
• (Q5053192) (← links)
• Approximate Degree in Classical and Quantum Computing (Q5060675) (← links)
• (Q5088989) (← links)
• Agnostically Learning Boolean Functions with Finite Polynomial Representation (Q5136248) (← links)
• A PAC Approach to Application-Specific Algorithm Selection (Q5269823) (← links)
• Concept learning by example decomposition (Q5306313) (← links)
• A comparative study of multi‐class support vector machines in the unifying framework of large margin classifiers (Q5467284) (← links)
• A Size-Sensitive Discrepancy Bound for Set Systems of Bounded Primal Shatter Dimension (Q5743609) (← links)
• Learning in Repeated Auctions (Q5863991) (← links)
• Deep learning: a statistical viewpoint (Q5887827) (← links)
• Finite sample properties of system identification of ARX models under mixing conditions (Q5926264) (← links)
• Improved bounds on the sample complexity of learning (Q5943102) (← links)
• Agnostic learning of geometric patterns (Q5943123) (← links)
• Nonlinear approximations using sets of finite cardinality or finite pseudo-dimension (Q5946398) (← links)
• Randomized algorithms for robust controller synthesis using statistical learning theory (Q5947623) (← links)
• Nonparametric regression function estimation using interaction least squares splines and complexity regularization. (Q5953727) (← links)
• Learning automata algorithms for pattern classification. (Q5955820) (← links)
• A comparison of identification criteria for inductive inference of recursive real-valued functions (Q5958650) (← links)
• Nonlinear approximation of functions by sets of finite pseudo-dimension in the probabilistic and average case settings (Q6085663) (← links)
• Learning with risks based on M-location (Q6097134) (← links)
• Minimax rates for conditional density estimation via empirical entropy (Q6117050) (← links)
• A survey of learning criteria going beyond the usual risk (Q6535427) (← links)
• Geometric problems in machine learning (Q6560225) (← links)
• Realizable learning is all you need (Q6566462) (← links)
• Statistical computational learning (Q6602226) (← links)