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 | 2012 | |
|---|---|---|
| j32 |      | Spencer K. White, Tony R. Martinez, George L. Rudolph: Automatic Algorithm Development Using New Reinforcement Programming Techniques. Computational Intelligence 28(2): 176-208 (2012) |
| j31 | | Michael Gashler, Tony R. Martinez: Robust manifold learning with CycleCut. Connect. Sci. 24(1): 57-69 (2012) |
| 2011 | ||
| j30 | | Michael Gashler, Dan Ventura, Tony R. Martinez: Manifold Learning by Graduated Optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B 41(6): 1458-1470 (2011) |
| c16 | | Adam H. Peterson, Tony R. Martinez, George L. Rudolph: On the structure of algorithm spaces. IJCNN 2011: 658-665 |
| c15 | | Michael Gashler, Tony R. Martinez: Temporal nonlinear dimensionality reduction. IJCNN 2011: 1959-1966 |
| c14 | | Michael Gashler, Tony R. Martinez: Tangent space guided intelligent neighbor finding. IJCNN 2011: 2617-2624 |
| c13 | | Kristine Monteith, James L. Carroll, Kevin D. Seppi, Tony R. Martinez: Turning Bayesian model averaging into Bayesian model combination. IJCNN 2011: 2657-2663 |
| c12 | | Michael R. Smith, Tony R. Martinez: Improving classification accuracy by identifying and removing instances that should be misclassified. IJCNN 2011: 2690-2697 |
| 2010 | ||
| j29 | | Adam H. Peterson, Tony R. Martinez: Using learning algorithm behavior to chart task space: The DICES distance. Intell. Data Anal. 14(3): 355-367 (2010) |
| c11 | | Spencer K. White, Tony R. Martinez, George L. Rudolph: Generating three binary addition algorithms using reinforcement programming. ACM Southeast Regional Conference 2010: 46 |
| c10 | | Spencer K. White, Tony R. Martinez, George L. Rudolph: Generating a novel sort algorithm using Reinforcement Programming. IEEE Congress on Evolutionary Computation 2010: 1-8 |
| c9 | | Kristine Monteith, Tony R. Martinez: Using multiple measures to predict confidence in instance classification. IJCNN 2010: 1-8 |
| 2009 | ||
| j28 | | Joshua E. Menke, Tony R. Martinez: Artificial neural network reduction through oracle learning. Intell. Data Anal. 13(1): 135-149 (2009) |
| j27 | | Adam H. Peterson, Tony R. Martinez: Reducing Decision Tree Ensemble Size Using Parallel Decision DAGs. International Journal on Artificial Intelligence Tools 18(4): 613-620 (2009) |
| j26 | | Joshua E. Menke, Tony R. Martinez: Improving Supervised Learning by Adapting the Problem to the Learner. Int. J. Neural Syst. 19(1): 1-9 (2009) |
| 2008 | ||
| j25 | | Joshua E. Menke, Tony R. Martinez: A Bradley-Terry artificial neural network model for individual ratings in group competitions. Neural Computing and Applications 17(2): 175-186 (2008) |
| c8 | | Michael Gashler, Christophe G. Giraud-Carrier, Tony R. Martinez: Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous. ICMLA 2008: 900-905 |
| 2007 | ||
| j24 | | Christophe G. Giraud-Carrier, Tony R. Martinez: Learning by Discrimination: A Constructive Incremental Approach. JCP 2(7): 49-58 (2007) |
| c7 | | Michael Gashler, Dan Ventura, Tony R. Martinez: Iterative Non-linear Dimensionality Reduction with Manifold Sculpting. NIPS 2007 |
| 2006 | ||
| j23 | | Michael Rimer, Tony R. Martinez: Classification-based objective functions. Machine Learning 63(2): 183-205 (2006) |
| j22 | | Michael Rimer, Tony R. Martinez: CB3: An Adaptive Error Function for Backpropagation Training. Neural Processing Letters 24(1): 81-92 (2006) |
| 2005 | ||
| c6 | | Joshua E. Menke, Tony R. Martinez: Domain expert approximation through oracle learning. ESANN 2005: 205-210 |
| 2004 | ||
| j21 | | Brent D. Morring, Tony R. Martinez: Weighted Instance Typicality Search (WITS): A nearest neighbor data reduction algorithm. Intell. Data Anal. 8(1): 61-78 (2004) |
| c5 | | Tony R. Martinez: Neural Networks and Machine Learning: Towards Fully Automated Learning. ENC 2004: 5 |
| 2003 | ||
| j20 | | D. Randall Wilson, Tony R. Martinez: The general inefficiency of batch training for gradient descent learning. Neural Networks 16(10): 1429-1451 (2003) |
| 2002 | ||
| j19 | | Ernest Istook, Tony R. Martinez: Improved Backpropagation Learning in Neural Networks with Windowed Momentum. Int. J. Neural Syst. 12(3-4): 303-318 (2002) |
| 2001 | ||
| j18 | | Xinchuan Zeng, Tony R. Martinez: An algorithm for correcting mislabeled data. Intell. Data Anal. 5(6): 491-502 (2001) |
| j17 | | Timothy L. Andersen, Tony R. Martinez: DMP3: A Dynamic Multilayer Perceptron Construction Algorithm. Int. J. Neural Syst. 11(2): 145-165 (2001) |
| 2000 | ||
| j16 | | D. Randall Wilson, Tony R. Martinez: An Integrated Instance-Based Learning Algorithm. Computational Intelligence 16(1): 1-28 (2000) |
| j15 | | |
| j14 | | Xinchuan Zeng, Tony R. Martinez: Distribution-balanced stratified cross-validation for accuracy estimation. J. Exp. Theor. Artif. Intell. 12(1): 1-12 (2000) |
| j13 | | D. Randall Wilson, Tony R. Martinez: Reduction Techniques for Instance-Based Learning Algorithms. Machine Learning 38(3): 257-286 (2000) |
| j12 | | Xinchuan Zeng, Tony R. Martinez: Using a Neural Network to Approximate an Ensemble of Classifiers. Neural Processing Letters 12(3): 225-237 (2000) |
| c4 | | D. Randall Wilson, Tony R. Martinez: The Inefficiency of Batch Training for Large Training Sets. IJCNN (2) 2000: 113-117 |
| c3 | | Xinchuan Zeng, Tony R. Martinez: Rescaling the Energy Function in Hopfield Networks. IJCNN (6) 2000: 498-504 |
| 1999 | ||
| j11 | | Xinchuan Zeng, Tony R. Martinez: A New Relaxation Procedure in the Hopfield Network for Solving Optimization Problems. Neural Processing Letters 10(3): 211-222 (1999) |
| 1997 | ||
| j10 | | D. Randall Wilson, Tony R. Martinez: Improved Heterogeneous Distance Functions. J. Artif. Intell. Res. (JAIR) 6: 1-34 (1997) |
| c2 |  | |
| i2 | | D. Randall Wilson, Tony R. Martinez: Improved Heterogeneous Distance Functions. CoRR cs.AI/9701101 (1997) |
| 1996 | ||
| j9 | | George L. Rudolph, Tony R. Martinez: LIA: A Location-Independent Transformation for ASOCS Adaptive Algorithm 2. Int. J. Neural Syst. 7(5): 639-654 (1996) |
| 1995 | ||
| j8 | | Christophe G. Giraud-Carrier, Tony R. Martinez: An Integrated Framework for Learning and Reasoning. J. Artif. Intell. Res. (JAIR) 3: 147-185 (1995) |
| j7 | | Christophe G. Giraud-Carrier, Tony R. Martinez: Analysis of the Convergence and Generalization of AA1. J. Parallel Distrib. Comput. 26(1): 125-131 (1995) |
| j6 | | George L. Rudolph, Tony R. Martinez: A transformation for implementing localist neural networks. Neural Parallel & Scientific Comp. 3(2): 173-187 (1995) |
| i1 | | Christophe G. Giraud-Carrier, Tony R. Martinez: An Integrated Framework for Learning and Reasoning. CoRR abs/cs/9508102 (1995) |
| 1994 | ||
| j5 | | Kevin S. Van Horn, Tony R. Martinez: The minimum feature set problem. Neural Networks 7(3): 491-494 (1994) |
| j4 | | J. C. Barker, Tony R. Martinez: Proof of correctness for ASOCS AA3 networks. IEEE Transactions on Systems, Man, and Cybernetics 24(3): 503-510 (1994) |
| 1991 | ||
| j3 | | Tony R. Martinez, Douglas M. Campbell: A Self-Adjusting Dynamic Logic Module. J. Parallel Distrib. Comput. 11(4): 303-313 (1991) |
| j2 | | Tony R. Martinez, Douglas M. Campbell: A self-organizing binary decision tree for incrementally defined rule-based systems. IEEE Transactions on Systems, Man, and Cybernetics 21(5): 1231-1238 (1991) |
| 1990 | ||
| c1 | | |
| 1988 | ||
| j1 | | Tony R. Martinez, Jacques J. Vidal: Adaptive Parallel Logic Networks. J. Parallel Distrib. Comput. 5(1): 26-58 (1988) |
Colors in the list of coauthors
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