Machine Learning

• Ben Marlin, Sam Roweis, and Richard Zemel (2004). "Unsupervised learning with non-ignorable missing data." To appear in: AISTATS 2005. pdf.

• Miguel Carreira-Perpinan and Richard Zemel (2004). "Proximity graphs for clustering and manifold learning." To appear in: NIPS-17: Advances in Neural Information Processing Systems 17. pdf (8 pages).

• Ben Marlin and Richard Zemel (2004). "The multiple multiplicative factor model for collaborative filtering." To appear in: ICML-2004: Proceedings of the 21st International Conference on Machine Learning. pdf (8 pages).

• Xuming He, Richard Zemel, and Miguel Carreira-Perpinan (2004). "Multiscale conditional random fields for image labelling." To appear in: CVPR-2004: IEEE Conference on Computer Vision and Pattern Recognition. gzipped postscript; pdf (8 pages).

• Max Welling, Richard Zemel, and Geoffrey Hinton (2004). "Probabilistic sequential independent components analysis." Transactions in Neural Networks , Special Issue on Information Theory. Accepted for publication.

• Craig Boutilier, Richard Zemel, and Benjamin Marlin (2003). "Active collaborative filtering." In: UAI-2003: 19th Conference on Uncertainty in Artificial Intelligence. gzipped postscript; pdf (9 pages).

• Max Welling, Richard Zemel, and Geoffrey Hinton (2003). "Efficient parametric projection pursuit density estimation." In: UAI-2003: 19th Conference on Uncertainty in Artificial Intelligence. gzipped postscript (8 pages).

• David Ross and Richard Zemel (2002). "Multiple-cause vector quantization." To appear in: NIPS-15: Advances in Neural Information Processing Systems 15. gzipped postscript; pdf (8 pages).

• Max Welling, Richard Zemel, and Geoffrey Hinton (2002). "Self supervised boosting." To appear in: NIPS-15: Advances in Neural Information Processing Systems 15. gzipped postscript; pdf (8 pages).

• Craig Boutilier and Richard Zemel (2002). "Online queries for collaborative filtering." In: Ninth International Workshop on Artificial Intelligence and Statistics . gzipped postscript; pdf (8 pages).

• Richard Zemel and Michael Mozer (2002). "Localist attractor networks." Neural Computation, 13(5), pp. 1045-1064. (pdf; gzipped postscript (20 pages).

• Richard Zemel and Toni Pitassi (2001). "A gradient-based boosting algorithm for regression problems." In: NIPS-13: Advances in Neural Information Processing Systems 13, pp. 696-702. gzipped postscript (7 pages).

• Geoffrey Hinton and Richard Zemel (1997). "Minimizing description length in an unsupervised neural network." gzipped postscript (22 pages).

• Peter Dayan and Richard Zemel (1995). "Competition and multiple cause models." Neural Computation, 7(3), pp. 565-579. gzipped postscript (15 pages).

• Peter Dayan, Geoffrey Hinton, Radford Neal, and Richard Zemel (1995). "The Helmholtz Machine." Neural Computation, 7(5), pp. 889-904.

• Richard Zemel, Chris Williams, and Michael Mozer (1995). "Lending direction to neural networks." Neural Networks, 8(4), pp. 503-512. gzipped postscript (20 pages).

• Richard Zemel and Geoffrey Hinton (1995). "Developing population codes by minimizing description length." Neural Computation, 7(3), pp. 549-564. gzipped postscript (14 pages).

• Richard Zemel (1994). "A Minimum Description Length Framework for Unsupervised Learning." Ph.D. Thesis. Technical Report CRG-TR-93-2, University of Toronto: In 3 separate sections: gzipped postscript1 (70 pages), gzipped postscript2 (20 pages), gzipped postscript3 (39 pages).

Neural Computation

• Richard Zemel, Quentin Huys, Rama Natarajan, and Peter Dayan (2004). "Probabilistic computation in spiking populationss." To appear in: NIPS-17: Advances in Neural Information Processing Systems 17. pdf (8 pages).

• Alex Pouget, Peter Dayan and Richard Zemel (2003). "Computation and inference with population codes." Annual Reviews of Neuroscience, 1, pp. 381-410. pdf (33 pages).

• Richard Zemel and Jon Pillow (2000). "Encoding multiple orientations in a recurrent network." Neurocomputing, 32-33, pp. 609-616. pdf (8 pages).

• Alex Pouget, Peter Dayan and Richard Zemel (2000). "Information processing with population codes." Nature Reviews Neuroscience, 1, pp. 125-132. pdf (8 pages).

• Richard Zemel (2000). "Cortical belief networks." To appear in R. Hecht-Neilsen (Ed.): Theories of the Cerebral Cortex. gzipped postscript (16 pages).

• Richard Zemel and Peter Dayan (1999). "Distributional population codes and multiple motion models." In NIPS-11: Advances in Neural Information Processing Systems 11, pp. 174-180. gzipped postscript (7 pages).

• Richard Zemel, Peter Dayan, and Alex Pouget (1998). "Probabilistic interpretation of population codes." Neural Computation, 10(2), pp. 403-430. (pdf (28 pages); gzipped postscript (25 pages).

• Richard Zemel and Terry Sejnowski (1998). "A model for encoding multiple object motions and self-motion in area MST of primate visual cortex." The Journal of Neuroscience, 18(1), pp. 531-547. pdf (17 pages).

• Richard Zemel and Peter Dayan (1997). "Combining probabilistic population codes." International Joint Conference on Artificial Intelligence 1997. Denver, CO: Morgan Kaufmann. gzipped postscript (6 pages).

Perceptual Learning and Attention

• Richard Zemel, Marlene Behrmann, Michael Mozer, and Daphne Bevalier (2002). "Experience-dependent perceptual grouping and object-based attention." Journal of Experimental Psychology: Human Perception and Performance, 28(1), pp. 202-217. gzipped postscript; pdf (16 pages).

• Marlene Behrmann, Richard Zemel, and Michael Mozer (2000). "Occlusion, symmetry, and object-based attention: Reply to Saiki (2000)." Journal of Experimental Psychology: Human Perception and Performance, 26(4), pp. 1497-1505.

• Zhiyong Yang and Richard Zemel (2000). "Managing uncertainty in cue combination." In: NIPS-12: Advances in Neural Information Processing Systems 12, pp. 80-86. gzipped postscript (7 pages).

• Marlene Behrmann, Richard Zemel, and Michael Mozer (1998). "Object-based attention and occlusion: Evidence from normal subjects and a computational model." Journal of Experimental Psychology: Human Perception and Performance, 24(4), pp. 1011-1036.

• Michael Mozer, Richard Zemel, Marlene Behrmann, and Chris Williams (1992). Learning to segment images using dynamic feature binding. Neural Computation, 4(5), pp. 647-662.