your friendly native guide
- H. J. Holz, K. Hofmann and C. Reed, “Chapter 2: Unobtrusive User Modeling for Adaptive Hypermedia, in Personalization Techniques and Recommender Systems”, vol. 70, G. Uchyigit and M. Y. Ma, Eds. World Scientific, 2008, 61-83.
- H. J. Holz, K. Hofmann and C. Reed, “Unobtrusive User Modeling for Adaptive Hypermedia”, International Journal of Pattern Recognition and Artificial Intelligence, vol. 21, no. 2, 225-244, 2007.
- H. Holz, A. G. Applin and W. Joel, “Status report of the SIGCSE committee on teaching computer science research methods”, in SIGCSE, 2007, 327-328.
- A. G. Applin, H. J. Holz, W. Joel, I. Okoye, K. Deibel, B. Grasser, B. J. Oates and G. Wood, “A multi-perspective digital library to facilitate integrating teaching research methods across the computing curriculum”, SIGCSE Bulletin, vol. 39, no. 4, 184-203, 2007.
- M. Jain, H. Holz, J. Shrager, O. Vallon, C. Hauser and A. Grossman, “A Hybrid, Recursive Algorithm for Clustering Expressed Sequence Tags in Chlamydomonas reinhardtii”, in ICPR (3), 2006, 404-407.
- K. Hofmann, C. Reed and H. J. Holz, “Unobtrusive Data Collection for Web-Based Social Navigation”, in Proceedings of the Workshop on Social Navigation and Community-Based Adaptive Technologies, AH ’06, 2006.
- H. J. Holz, A. Applin, B. Haberman, D. Joyce, H. Purchase and C. Reed, “Research methods in computing: what are they, and how should we teach them?”, SIGCSE Bulletin, vol. 38, no. 4, 96-114, 2006.
- J. Beidler, H. Holz, K. Yasuhara and E. J. Adams, “The many facets of diversity”, in Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education, 2005, 558-559.
- T. Henry, H. J. Holz, C. Steinback, C. Reed and A. Baid, “Work in progress-student retention and recruitment in computer science programs”, in Frontiers in Education 2004, 2004, vol. 2, F3C - 13-14.
- J. Farrell and H. J. Holz, “Enki: open infrastructure for adaptive digital libraries”, in Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2002, 391.
- H. J. Holz and M. H. Loew, “Validation of relative feature importance using natural data”, Pattern Recognition Letters, vol. 23, no. 4, 367-380, 2002.
- H. J. Holz, D. B. Russakoff, H. Abbasi, D. H. Kim, G. Steinberg and R. Shahidi, “Expected versus observed error in a computer-aided navigation system for spine surgery”, in Proceedings of the 15th International Congress and Exhibition on Computer Assisted Radiology and Surgery, 2001, 112-116.
- H. Abbasi, R. P. Grzeszczuk, S. Chin, H. J. Holz, S. Hariri, R. Badr, D. H. Kim, J. R. A. Jr. and R. Shahidi, “Development of fluoroscopic registration in spinal neuronavigation”, in Proceedings of the 15th International Congress and Exhibition on Computer Assisted Radiology and Surgery, 2001, 1236-1238.
- H. J. Holz and M. H. Loew, “Validation of Relative Feature Importance Using a Natural Data Set”, in Proceedings of the 15th International Conference on Pattern Recognition, 2000, 2414-2417.
- H. J. Holz and M. H. Loew, “Design Choices and Theoretical Issues for Relative Feature Importance, a Metric for Nonparametric Discriminatory Power”, in SSPR/SPR, 2000, 696-705.
- R. P. Grzeszczuk, S. Chin, R. Fahrig, H. Abbasi, H. J. Holz, D. H. Kim, J. R. A. Jr. and R. Shahidi, “A Flouroscopic X-Ray Registration Process for Three-Dimensional Surgical Navigation”, in MICCAI, 2000, 551-556.
- H. J. Holz, “Classifier-Independent Feature Analysis”, Washington, DC, 1999.
- H. J. Holz and M. H. Loew, “Multi-class classifier-independent feature analysis”, Pattern Recognition Letters, vol. 18, no. 11, 1219-1224, 1997.
- H. J. Holz and M. H. Loew, “Concurrency in Feature Analysis”, in Applied Parallel Computing, Computations in Physics, Chemistry and Engineering Science, 1996, 313-322.
- H. J. Holz and M. H. Loew, “Relative Feature Importance: A Classifier-Independent Approach to Feature Selection”, in Pattern Recognition in Practice IV, E. S. Gelsema and L. N. Kanal, Eds. Amsterdam: Elsevier, 1994, 473-487.
- H. J. Holz and M. H. Loew, “Non-parametric discriminatory power”, in Proceedings of the 1994 IEEE-IMS Workshop on Information Theory and Statistics, 1994, 65.
- C. D. Martin and H. J. Holz, “Non-apologetic computer ethics education: a strategy for integrating social impact and ethics into the computer science curriculum”, in Teaching computer ethics, T. W. Bynum, W. Maner and J. L. Fodor, Eds. New Haven, CT, USA: Southern Connecticut State University, 1992, 50-66.
- C. D. Martin and H. J. Holz, “Integrating Social Impact and Ethics Issues Across the Computer Science Curriculum”, Education and Society, vol. 2, 137-143, 1992.
- G. Bailey, R. Demeo, H. J. Holz and J. Revell, “Survival of the Fittest”, in Proceedings of the Workshop on Evolution and Chaos in Cognitive Processing, International Joint Conference on Artificial Intelligence, 1991.
- P. Bock, H. Holz, R. Rovner and C. J. Kocinski, “An initial performance evaluation of unsupervised learning with ALIAS”, in International Joint Conference on Neural Networks, 1990, vol. 1, 451-465.
- P. Bock, R. Rovner, C. J. Kocinski, H. J. Holz and G. Becker, “A parallel implementation of collective learning systems theory: Adaptive Learning Image Analysis System (ALIAS)”, in CSC ’90: Proceedings of the 1990 ACM annual conference on Cooperation, 1990, 457-469.
- P. Bock, G. Becker, H. J. Holz, C. J. Kocinski and R. Rovner, “An Application of Collective Learning Systems Theory to an Adaptive Learning Image Analysis System: Project ALIAS”, in Neuro-Nimes ’89: International Workshop on Neural Networks and Their Applications, 1989, 1-12.