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Michael Mozer
List of publications from the DBLP Bibliography Server - FAQ
| 2009 | ||
|---|---|---|
| 53 | EE | Dan Knights, Todd Mytkowicz, Peter F. Sweeney, Michael C. Mozer, Amer Diwan: Blind Optimization for Exploiting Hardware Features. CC 2009: 251-265 |
| 2008 | ||
| 52 | EE | Jeremy Reynolds, Michael C. Mozer: Temporal Dynamics of Cognitive Control. NIPS 2008: 1353-1360 |
| 51 | EE | Matt Jones, Michael C. Mozer, Sachiko Kinoshita: Optimal Response Initiation: Why Recent Experience Matters. NIPS 2008: 785-792 |
| 50 | EE | Michael C. Mozer, Adrian Fan: Top-Down modulation of neural responses in visual perception: a computational exploration. Natural Computing 7(1): 45-55 (2008) |
| 2007 | ||
| 49 | EE | Michael Mozer, David Baldwin: Experience-Guided Search: A Theory of Attentional Control. NIPS 2007 |
| 48 | EE | Sander M. Bohte, Michael C. Mozer: Reducing the Variability of Neural Responses: A Computational Theory of Spike-Timing-Dependent Plasticity. Neural Computation 19(2): 371-403 (2007) |
| 2006 | ||
| 47 | EE | Michael C. Mozer, Michael Jones, Michael Shettel: Context Effects in Category Learning: An Investigation of Four Probabilistic Models. NIPS 2006: 993-1000 |
| 46 | EE | Michael C. Mozer: Rational Models of Cognitive Control. UC 2006: 20-25 |
| 2005 | ||
| 45 | Sander M. Bohte, Michael C. Mozer: Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity. BNAIC 2005: 319-320 | |
| 44 | EE | Michael Mozer, Michael Shettel, Shaun Vecera: Top-Down Control of Visual Attention: A Rational Account. NIPS 2005 |
| 43 | EE | Matthias Hauswirth, Amer Diwan, Peter F. Sweeney, Michael C. Mozer: Automating vertical profiling. OOPSLA 2005: 281-296 |
| 2004 | ||
| 42 | EE | Michael Mozer: How Practice Makes Perfect. ICCM 2004: 13-13 |
| 41 | EE | Sander M. Bohte, Michael C. Mozer: Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity. NIPS 2004 |
| 40 | EE | Michael D. Colagrosso, Michael C. Mozer: Theories of Access Consciousness. NIPS 2004 |
| 2003 | ||
| 39 | Lian Yan, Robert H. Dodier, Michael Mozer, Richard H. Wolniewicz: Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic. ICML 2003: 848-855 | |
| 2002 | ||
| 38 | EE | Sepp Hochreiter, Michael Mozer, Klaus Obermayer: Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. NIPS 2002: 545-552 |
| 2001 | ||
| 37 | EE | Sepp Hochreiter, Michael Mozer: A Discrete Probabilistic Memory Model for Discovering Dependencies in Time. ICANN 2001: 661-668 |
| 36 | EE | Michael C. Mozer, Robert H. Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard H. Wolniewicz: Prodding the ROC Curve: Constrained Optimization of Classifier Performance. NIPS 2001: 1409-1415 |
| 35 | EE | Michael C. Mozer, Michael D. Colagrosso, David E. Huber: A Rational Analysis of Cognitive Control in a Speeded Discrimination Task. NIPS 2001: 51-57 |
| 34 | Richard S. Zemel, Michael Mozer: Localist Attractor Networks. Neural Computation 13(5): 1045-1064 (2001) | |
| 2000 | ||
| 33 | David B. Grimes, Michael Mozer: The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving. NIPS 2000: 17-23 | |
| 32 | Sepp Hochreiter, Michael Mozer: Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models. NIPS 2000: 535-541 | |
| 1999 | ||
| 31 | EE | Soo-Young Lee, Michael Mozer: Robust Recognition of Noisy and Superimposed Patterns via Selective Attention. NIPS 1999: 31-37 |
| 30 | EE | Richard S. Zemel, Michael Mozer: A Generative Model for Attractor Dynamics. NIPS 1999: 80-88 |
| 29 | EE | Michael Mozer, Richard H. Wolniewicz, David B. Grimes, Eric Johnson, Howard Kaushansky: Churn Reduction in the Wireless Industry. NIPS 1999: 935-941 |
| 28 | EE | Jay A. Alexander, Michael Mozer: Template-based procedures for neural network interpretation. Neural Networks 12(3): 479-498 (1999) |
| 1998 | ||
| 27 | EE | Michael Mozer: A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes. NIPS 1998: 52-58 |
| 26 | EE | Sreerupa Das, Michael Mozer: Dynamic On-line Clustering and State Extraction: An Approach to Symbolic Learning. Neural Networks 11(1): 53-64 (1998) |
| 1997 | ||
| 25 | Michael Mozer, Michael I. Jordan, Thomas Petsche: Advances in Neural Information Processing Systems 9, NIPS, Denver, CO, USA, December 2-5, 1996 MIT Press 1997 | |
| 24 | Michael Mozer, Mark Sitton, Martha J. Farah: A Superadditive-Impairment Theory of Optic Aphasia. NIPS 1997 | |
| 23 | EE | Michael Mozer, Debra Miller: Parsing the Stream of Time: The Value of Event-Based Segmentation in a Complex Real-World Control Problem. Summer School on Neural Networks 1997: 370-388 |
| 22 | EE | Brad Calder, Dirk Grunwald, Michael P. Jones, Donald C. Lindsay, James H. Martin, Michael Mozer, Benjamin G. Zorn: Evidence-Based Static Branch Prediction Using Machine Learning. ACM Trans. Program. Lang. Syst. 19(1): 188-222 (1997) |
| 1996 | ||
| 21 | David S. Touretzky, Michael Mozer, Michael E. Hasselmo: Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, November 27-30, 1995 MIT Press 1996 | |
| 20 | EE | Michael Mozer, Lucky Vidmar, Robert H. Dodier: The Neurothermostat: Predictive Optimal Control of Residential Heating Systems. NIPS 1996: 953-959 |
| 1995 | ||
| 19 | Brad Calder, Dirk Grunwald, Donald C. Lindsay, James H. Martin, Michael Mozer, Benjamin G. Zorn: Corpus-Based Static Branch Prediction. PLDI 1995: 79-92 | |
| 18 | EE | Richard S. Zemel, Christopher K. I. Williams, Michael Mozer: Lending direction to neural networks. Neural Networks 8(4): 503-512 (1995) |
| 1994 | ||
| 17 | EE | Donald W. Mathis, Michael Mozer: On the Computational Utility of Consciousness. NIPS 1994: 11-18 |
| 16 | EE | Jay A. Alexander, Michael Mozer: Template-Based Algorithms for Connectionist Rule Extraction. NIPS 1994: 609-616 |
| 1993 | ||
| 15 | Clayton McMillan, Michael Mozer, Paul Smolensky: Dynamic Conflict Resolution in a Connectionist Rule-Based System. IJCAI 1993: 1366-1373 | |
| 14 | EE | Sreerupa Das, Michael Mozer: A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction. NIPS 1993: 19-26 |
| 1992 | ||
| 13 | EE | Brian V. Bonnlander, Michael Mozer: Metamorphosis Networks: An Alternative to Constructive Models. NIPS 1992: 131-138 |
| 12 | EE | Richard S. Zemel, Christopher K. I. Williams, Michael Mozer: Directional-Unit Boltzmann Machines. NIPS 1992: 172-179 |
| 11 | EE | Michael Mozer, Sreerupa Das: A Connectionist Symbol Manipulator that Discovers the Structure of Context-Free Languages. NIPS 1992: 863-870 |
| 1991 | ||
| 10 | EE | Michael Mozer: Induction of Multiscale Temporal Structure. NIPS 1991: 275-282 |
| 9 | EE | Michael Mozer, Richard S. Zemel, Marlene Behrmann: Learning to Segment Images Using Dynamic Feature Binding. NIPS 1991: 436-443 |
| 8 | EE | Clayton McMillan, Michael Mozer, Paul Smolensky: Rule Induction through Integrated Symbolic and Subsymbolic Processing. NIPS 1991: 969-976 |
| 7 | Michael Mozer: Neural network music composition and the induction of multiscale temporal structure. Wissensbasierte Systeme 1991: 448-458 | |
| 6 | Michael Mozer, Jonathan Bachrach: SLUG: A Connectionist Architecture for Inferring the Structure of Finite-State Environments. Machine Learning 7: 139-160 (1991) | |
| 1990 | ||
| 5 | EE | Michael Mozer: Discovering Discrete Distributed Representations. NIPS 1990: 627-634 |
| 4 | EE | Michael Mozer, Todd Soukup: Connectionist Music Composition Based on Melodic and Stylistic Constraints. NIPS 1990: 789-796 |
| 1989 | ||
| 3 | EE | Richard S. Zemel, Michael Mozer, Geoffrey E. Hinton: TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations. NIPS 1989: 266-273 |
| 2 | EE | Michael Mozer, Jonathan Bachrach: Discovering the Structure of a Reactive Environment by Exploration. NIPS 1989: 439-446 |
| 1988 | ||
| 1 | EE | Michael Mozer, Paul Smolensky: Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment. NIPS 1988: 107-115 |