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| Vacillatory learning of nearly-minimal size grammars - John Case, Sanjay Jain and Arun Sharma - 1994 |
| The Valiant Learning Model: Extensions and Assessment - J. Amsterdam - January 1988 |
| Valid Generalisation of Functions from Close Approximations on a Sample - M. Anthony and J. Shawe-Taylor - 1994 |
| The Vapnik-Chervonenkis Dimension: Information verses Complexity in Learning - Y. S. Abu-Mostafa - 1989 |
| Vapnik-Chervonenkis dimension of recurrent neural networks - Pascal Koiran and Eduardo D. Sontag - 1997 |
| VC dimension of an integrate-and-fire neuron model - Anthony M. Zador and Barak A. Pearlmutter - 1996 |
| The VC dimensions of finite automata with n states - Y. Ishigami and S. Tani - 1993 |
| The VC-dimension vs. the statistical capacity for two layer networks with binary weights - C. Ji and D. Psaltis - 1991 |
| Vector Quantization in Speech Coding - J. Makhoul, S. Roucos and H. Gish - November 1985 |
| A Version Space Approach to Learning Context-free Grammars - Kurt Vanlehn and William Ball - 1987 |
| Version Spaces: A Candidate Elimination Approach to Rule Learning - T. M. Mitchell - August 1977 |
| Very Simple Classification Rules Perform Well on Most Commonly Used Datasets - Robert C. Holte - 1993 |
| A view of computational learning theory - Leslie Valiant - 1991 |
| Visualizing high-dimensional structure with the incremental grid-growing neural network - Justine Blackmore and Risto Miikkulainen - 1995 |
| Volume of Polyhedra - R. Seidel - 1995 |