Volume 65, Number 1, October 2006
- Shi Zhong:
Semi-supervised model-based document clustering: A comparative study.
3-29

- Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis:
The max-min hill-climbing Bayesian network structure learning algorithm.
31-78

- Maria-Florina Balcan, Avrim Blum, Santosh Vempala:
Kernels as features: On kernels, margins, and low-dimensional mappings.
79-94

- Chris Drummond, Robert C. Holte:
Cost curves: An improved method for visualizing classifier performance.
95-130

- Marc Boullé:
MODL: A Bayes optimal discretization method for continuous attributes.
131-165

- Abraham P. George, Warren B. Powell:
Adaptive stepsizes for recursive estimation with applications in approximate dynamic programming.
167-198

- Y. Xiang, J. Lee:
Learning decomposable markov networks in pseudo-independent domains with local evaluation.
199-227

- Dougu Nam, Seunghyun Seo, Sangsoo Kim:
An efficient top-down search algorithm for learning Boolean networks of gene expression.
229-245

- E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao:
An analysis of diversity measures.
247-271

- Kar-Ann Toh:
Training a reciprocal-sigmoid classifier by feature scaling-space.
273-308

- Rajesh Pampapathi, Boris Mirkin, Mark Levene:
A suffix tree approach to anti-spam email filtering.
309-338

Volume 65, Numbers 2-3, December 2006
Special Issue on Machine Learning in and for Music
- Gerhard Widmer:
Guest editorial: Machine learning in and for music.
343-346

- Gerhard Widmer:
Guest Editorial: Machine learning in and for music.
347

- Darrell Conklin:
Melodic analysis with segment classes.
349-360

- Graham Grindlay, David P. Helmbold:
Modeling, analyzing, and synthesizing expressive piano performance with graphical models.
361-387

- Christopher Raphael:
Aligning music audio with symbolic scores using a hybrid graphical model.
389-409

- Maarten Grachten, Josep Lluís Arcos, Ramon López de Mántaras:
A case based approach to expressivity-aware tempo transformation.
411-437

- Daniel P. W. Ellis, Graham E. Poliner:
Classification-based melody transcription.
439-456

- Ning Hu, Roger B. Dannenberg:
Bootstrap learning for accurate onset detection.
457-471

- James Bergstra, Norman Casagrande, Dumitru Erhan, Douglas Eck, Balázs Kégl:
Aggregate features and ADABOOSTfor music classification.
473-484

- Samer A. Abdallah, Mark B. Sandler, Christophe Rhodes, Michael Casey:
Using duration models to reduce fragmentation in audio segmentation.
485-515

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