The following pages link to A theory of the learnable (Q3714486):
Displaying 50 items.
- The Perceptron algorithm versus Winnow: linear versus logarithmic mistake bounds when few input variables are relevant (Q1127362) (← links)
- Knowing what doesn't matter: exploiting the omission of irrelevant data (Q1127363) (← links)
- Partial Occam's Razor and its applications (Q1127393) (← links)
- Schema induction for logic program synthesis (Q1128483) (← links)
- On convergence proofs in system identification -- a general principle using ideas from learning theory (Q1128973) (← links)
- Learning regular languages from counterexamples (Q1176104) (← links)
- The Vapnik-Chervonenkis dimension of decision trees with bounded rank (Q1182084) (← links)
- Equivalence of models for polynomial learnability (Q1183606) (← links)
- Learning elementary formal systems (Q1186429) (← links)
- Efficient learning of context-free grammars from positive structural examples (Q1186808) (← links)
- Learning in parallel (Q1187024) (← links)
- Principles of metareasoning (Q1187348) (← links)
- Inductive reasoning and Kolmogorov complexity (Q1190991) (← links)
- On the necessity of Occam algorithms (Q1193631) (← links)
- Nested annealing: A provable improvement to simulated annealing (Q1193895) (← links)
- Learning convex bodies under uniform distribution (Q1198007) (← links)
- Rank-\(r\) decision trees are a subclass of \(r\)-decision lists (Q1198056) (← links)
- Decision theoretic generalizations of the PAC model for neural net and other learning applications (Q1198550) (← links)
- Structure identification in relational data (Q1204870) (← links)
- IIPS: A framework for specifying inductive-inference problems (Q1206224) (← links)
- Bounding sample size with the Vapnik-Chervonenkis dimension (Q1209149) (← links)
- The degree of approximation of sets in euclidean space using sets with bounded Vapnik-Chervonenkis dimension (Q1265746) (← links)
- Learning approximately regular languages with reversible languages (Q1269920) (← links)
- Neural networks as systems for recognizing patterns (Q1270539) (← links)
- General bounds on statistical query learning and PAC learning with noise via hypothesis boosting (Q1271468) (← links)
- Optimal mistake bound learning is hard (Q1271479) (← links)
- Specification and simulation of statistical query algorithms for efficiency and noise tolerance (Q1271551) (← links)
- Learning with unreliable boundary queries (Q1271553) (← links)
- Learning with restricted focus of attention (Q1271613) (← links)
- Double Horn functions (Q1271644) (← links)
- An introduction to some statistical aspects of PAC learning theory (Q1274408) (← links)
- Learning dynamical systems in a stationary environment (Q1274409) (← links)
- A probabilistic framework for memory-based reasoning (Q1274693) (← links)
- Sample size lower bounds in PAC learning by Algorithmic Complexity Theory (Q1274920) (← links)
- On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems (Q1274926) (← links)
- Approximating hyper-rectangles: Learning and pseudorandom sets (Q1278043) (← links)
- PAC-learning a decision tree with pruning (Q1278327) (← links)
- Noise-tolerant parallel learning of geometric concepts (Q1281499) (← links)
- Synthesizers and their application to the parallel construction of pseudo-random functions (Q1288205) (← links)
- On the boosting ability of top-down decision tree learning algorithms (Q1305926) (← links)
- On the learnability of rich function classes (Q1305934) (← links)
- A general frmework for supervised learning. Probably almost Bayesian algorithms (Q1309836) (← links)
- Combinatorics and connectionism (Q1313821) (← links)
- A result of Vapnik with applications (Q1314333) (← links)
- Generating logical expressions from positive and negative examples via a branch-and-bound approach (Q1318514) (← links)
- Extremes in the degrees of inferability (Q1319507) (← links)
- Modeling a dynamic environment using a Bayesian multiple hypothesis approach (Q1327165) (← links)
- Dynamic sizing of multilayer perceptrons (Q1328141) (← links)
- Efficient distribution-free learning of probabilistic concepts (Q1329154) (← links)
- Nonuniform learnability (Q1329161) (← links)
