GURU Publications

The focus of research in GURU is the workings of real and artificial neural networks. A selection of our publications is given below, indexed first by subject and then by author.

Indexed by Subject

Adaptive Information Retrieval

Vogt CC (1999). Adaptive combination of evidence for information retrieval. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Vogt CC and Cottrell GW (1999). Fusion via a linear combination of scores (preprint). Information Retrieval 1(3):151-173.

Vogt CC and Cottrell GW (1998). Predicting the performance of linearly combined IR systems. Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

Vogt CC, Cottrell GW, Belew RK, and Bartell BT (1999). User lenses - Achieving 100% precision on frequently asked questions. Proceedings of User Modeling '99, Banff, pp. 87-96.

Bartell BT (1994). Optimizing ranking functions: A connectionist approach to adaptive information retrieval. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Bartell BT, Cottrell GW, and Belew RK (1998). Optimizing similarity using multi-query relevance feedback. Journal of the American Society for Information Science 49(8):742-61.

Bartell BT, Cottrell GW, and Belew RK (1998). Representing documents using an explicit model of their similarities. Journal of the American Society for Information Science 46(4):254-71.

Bartell BT, Cottrell GW, and Belew RK (1992). Latent semantic indexing is an optimal special case of multidimensional scaling. Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

Cross Validation/Training Set Optimization

Plutowski ME (1994). Selecting training exemplars for neural network learning. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Plutowski ME, Cottrell GW, and White H (1994). Learning Mackey glass from 25 examples, plus or minus 2. Advances in Neural Information Processing Systems 6.

Dimensionality Reduction, Face Recognition & Image Compression

Cottrell GW, Dailey MN, Padgett C, and Adolphs R (2000). Is all face processing holistic? The view from UCSD. In M Wenger and J Townsend (Eds), Computational, Geometric, and Process Perspectives on Facial Cognition: Contexts and Challenges. Erlbaum.

Dailey MN and Cottrell GW (1999). Organization of Face and Object Recognition in Modular Neural Networks. Neural Networks 12(7-8):1053-1074.

Dailey MN, Cottrell GW, and Busey TA (1998). Facial memory is kernel density estimation (almost). Advances in Neural Information Processing Systems 11.

Padgett C and Cottrell GW (1998). A simple neural network models categorical perception of facial expressions. Proceedings of the Twentieth Annual Cognitive Science Conference. (Here's Figure 3; we can't get it to print properly in the paper!)

Dailey MN, Cottrell GW, and Busey TA (1998). Eigenfaces for familiarity. Proceedings of the Twentieth Annual Cognitive Science Conference.

Dailey MN and Cottrell GW (1997). Task and spatial frequency effects on face specialization. Advances in Neural Information Processing Systems 10.

Dailey MN, Cottrell GW, and Padgett C (1997). A mixture of experts model exhibiting prosopagnosia. Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society.

Sugimoto MX (2000). Visual expertise is a general skill. Master's Thesis, Department of Computer Science and Engineering, University of California, San Diego.

Padgett C (1998). A neural network model for facial affect classification. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Padgett C, Cottrell GW, and Adolphs R (1996). Categorical Perception in facial emotion classification. Proceedings of the Eighteenth Annual Conference Of The Cognitive Science Society.

DeMers D and Cottrell GW (1993). Nonlinear dimensionality reduction. Advances in Neural Information Processing Systems 5.

Instructable Connectionist Models

Noelle DC (1997). A connectionist model of instructed learning. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Noelle DC, Cottrell GW, and Wilms FR (1997). Extreme attraction: On the discrete representation preference of attractor networks. Proceedings of the 19th Annual Conference Of The Cognitive Science Society.

Noelle DC and Cottrell GW (1996). In search of articulated attractors. Proceedings of the 18th Annual Conference Of The Cognitive Science Society.

Noelle DC and Cottrell GW (1996). Modeling interference effects in instructed category learning. Proceedings of the 18th Annual Conference Of The Cognitive Science Society.

Noelle D and Cottrell G (1994). Towards Instructable Connectionist Systems. Computational Architectures Integrating Neural And Symbolic Processes. Kluwer Academic Publishers, Boston.

Learning to Read Aloud

Milostan JC (1999). Why Johnny can read: The role of statistical regularities in reading and connectionist modeling. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Milostan JC and Cottrell GW (1997). Serial position in single word pronunciation: Connectionist models and neighborhood structure. Advances in Neural Information Processing Systems 10.

Lexical Access and Language Induction

Clouse DS (1998). Representing lexical semantics with context vectors and modeling lexical access with attractor networks. Ph.D. Thesis, Department of Computer Science and Engineering, University of California, San Diego.

Clouse DS and Cottrell GW (1998). Regularities in a random mapping from orthography to semantics. Proceedings of the Twentieth Annual Cognitive Science Conference.

Jackson D, Constandse RM, and Cottrell GW (1996). Selective attention in the acquisition of the past tense. Proceedings of the 18th Annual Conference Of The Cognitive Science Society.

Clouse DS and Cottrell GW (1996). Discrete multi-dimensional scaling. Proceedings of the 18th Annual Conference Of The Cognitive Science Society.

Cottrell GW and Plunkett K (1994). Acquiring the mapping from meanings to sounds. Connection Science 6(4): 379-412.

Neurobiology of Leech Behavior

Taylor AL, Kristan WB, and Cottrell, GW (2000). A model of the leech segmental swim central pattern generator. Neurocomputing 32-33, pp. 573-584.

Qualia

Laakso A (1999). The significance of spatial representation. Ph.D. Thesis, Department of Philosophy, The University of California, San Diego.

Laakso A and Cottrell GW (1998). How can I know what you think?: Assessing representational similarity in neural systems. Proceedings of the Twentieth Annual Cognitive Science Conference.

Laakso A and Cottrell GW (2000). Content and cluster analysis: Assessing representational similarity in neural systems. Philosophical Psychology 13(1).

Recurrent Networks and Dynamical Systems

Tsung F-S and Cottrell GW (1993). Phase-space learning in recurrent networks. Technical Report CS93-285, Department of Computer Science and Engineering, University of California, San Diego.

Speech Production

Anderson K, Milostan JC, and Cottrell GW (1998). Assessing the contribution of representation to results. Proceedings of the Twentieth Annual Cognitive Science Conference.

Smith MA, Cottrell GW, and Anderson KL (2001). The early word catches the weights. Advances in Neural Information Processing Systems 12 (to appear).

Speech Recognition

Nguyen MH (1995). Modeling dynamic signals with neural networks. Ph.D. Thesis, Department of Computer Science and Engineering, The University of California, San Diego.

Nguyen MH and Cottrell GW (1996). Tau Net: A neural network for modeling temporal variability. Neurocomputing 15:249-271.

Indexed by Author