 | Wastewater Treatment Systems from Case-Based Reasoning - Srinivas Krovvidy and William G. Wee - 1993 |
| WBCSVM: Weighted Bayesian Classification Based on Support Vector Machines - Thomas Gärtner and Peter A. Flach - 2001 |
| Weakening the language bias in LINUS - N. Lavrac and S. Džeroski - 1994 |
| Weakly Learning DNF and Characterizing Statistical Query Learning Using Fourier Analysis - A. Blum, M. Furst, J. Jackson, M. Kearns, Y. Mansour and S. Rudich - 1994 |
| The weighted majority algorithm - N. Littlestone and M. K. Warmuth - 1994 |
| A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features - Scott Cost and Steven Salzberg - 1993 |
| Weight elimination and effective network size - Andreas S. Weigend and David E. Rumelhart - 1994 |
| Well-behaved Borgs, Bolos, and Berserkers - Diana F. Gordon - 1998 |
| What can we learn from the web? - William W. Cohen - 1999 |
| What Connectionist Models Learn: Learning and Representation in Connectionist Networks - S. J. Hanson and D. J. Burr - 1990 |
| What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation - Stephanie Forrest and Melanie Mitchell - 1993 |
| What makes derivational analogy work: an experience report using APU - Sanjay Bhansali and Mehdi T. Harandi - 1997 |
| What Size Net Gives Valid Generalization? - E. Baum and D. Haussler - 1989 |
| When are k-nearest neighbor and backpropagation accurate for feasible-sized sets of examples? - Eric. B. Baum - 1994 |
| When Can Two Unsupervised Learners Achieve PAC Separation? - Paul W. Goldberg - 2001 |
| When oracles do not help - T. A. Slaman and R. M. Solovay - 1991 |
| When Will Machines Learn? - Douglas B. Lenat - 1989 |
| When won't membership queries help? - Dana Angluin and Michael Kharitonov - 1995 |
| Which classes of elementary formal systems are polynomial-time learnable? - S. Miyano, A. Shinohara and T. Shinohara - 1992 |
| Why Discretization Works for Na\"ıve Bayesian Classifiers - Chun-Nan Hsu, Hung-Ju Huang and Tzu-Tsung Wong - 2000 |
| Why experimentation can be better than Perfect Guidance - Tobias Scheffer, Russell Greiner and Christian Darken - 1997 |
| Why Should Machines Learn? - H. A. Simon - 1983 |
| A Winnow-Based Approach to Context-Sensitive Spelling Correction - Andrew R. Golding and Dan Roth - 1999 |
| The World Would Be a Better Place if Non-Programmers Could Program - John McDermott - 1989 |
| Worst-Case Bounds for the Logarithmic Loss of Predictors - Nicolò Cesa-Bianchi and Gábor Lugosi - 2001 |
| Worst-Case Loss Bounds for Single Neurons - David P. Helmbold, Jyrki Kivinen and Manfred K. Warmuth - 1996 |
| Worst-case quadratic loss bounds for a generalization of the Widrow-Hoff rule - N. Cesa-Bianchi, P. Long and M. Warmuth - 1993 |
| Worst-case quadratic loss bounds for on-line prediction of linear functions by gradient descent - N. Cesa-Bianchi, P. M. Long and M. K. Warmuth - 1996 |
| Wrapper Generation via Grammar Induction - Boris Chidlovskii, Jon Ragetli and Maarten de Rijke - 2000 |
| Wrapping Web Information Providers by Transducer Induction - Boris Chidlovskii - 2001 |
| WWW Visualization Tools for Discovering Interesting Web Pages - Hironori Hiraishi and Fumio Mizoguchi - 2001 |
| X-means: Extending K-means with Efficient Estimation of the Number of Clusters - Dan Pelleg and Andrew Moore - 2000 |
| Zur algorithmischen Synthese von schnellen Programmen - Thomas Zeugmann - 1983 |
| Zur Charakterisierung von Erkennungssytemen mit einbettendem Konvergenzbegriff - H. Thiele - 1975 |
| Zur Kompliziertheit der konsistenten Erkennung von Klassen allgemein-rekursiver Funktionen - P. J. Klaus - 1976 |
| Zur Konvergenzgeschwindigkeit von Strategien der induktiven Inferenz - H. R. Beick - 1982 |
| Zur Theorie der Algorithmischen Erkennung - R. Wiehagen - 1978 |
| Zur Untersuchung von Abstrakten Interaktiven Erkennungssystemen - H. Jung - 1977 |
