Tony R. Martinez

	2012
47		Michael Gashler, Tony R. Martinez: Robust manifold learning with CycleCut. Connect. Sci. 24(1): 57-69 (2012)
	2011
46		Michael Gashler, Tony R. Martinez: Temporal nonlinear dimensionality reduction. IJCNN 2011: 1959-1966
45		Michael Gashler, Tony R. Martinez: Tangent space guided intelligent neighbor finding. IJCNN 2011: 2617-2624
44		Kristine Monteith, James L. Carroll, Kevin D. Seppi, Tony R. Martinez: Turning Bayesian model averaging into Bayesian model combination. IJCNN 2011: 2657-2663
43		Michael R. Smith, Tony R. Martinez: Improving classification accuracy by identifying and removing instances that should be misclassified. IJCNN 2011: 2690-2697
42		Adam H. Peterson, Tony R. Martinez, George L. Rudolph: On the structure of algorithm spaces. IJCNN 2011: 658-665
41		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)
	2010
40		Spencer K. White, Tony R. Martinez, George L. Rudolph: Generating three binary addition algorithms using reinforcement programming. ACM Southeast Regional Conference 2010: 46
39		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
38		Kristine Monteith, Tony R. Martinez: Using multiple measures to predict confidence in instance classification. IJCNN 2010: 1-8
37		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)
	2009
36		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)
35		Joshua E. Menke, Tony R. Martinez: Artificial neural network reduction through oracle learning. Intell. Data Anal. 13(1): 135-149 (2009)
34		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)
	2008
33		Michael Gashler, Christophe G. Giraud-Carrier, Tony R. Martinez: Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous. ICMLA 2008: 900-905
32		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)
	2007
31		Michael Gashler, Dan Ventura, Tony R. Martinez: Iterative Non-linear Dimensionality Reduction with Manifold Sculpting. NIPS 2007
30		Christophe G. Giraud-Carrier, Tony R. Martinez: Learning by Discrimination: A Constructive Incremental Approach. JCP 2(7): 49-58 (2007)
	2006
29		Michael Rimer, Tony R. Martinez: Classification-based objective functions. Machine Learning 63(2): 183-205 (2006)
28		Michael Rimer, Tony R. Martinez: CB3: An Adaptive Error Function for Backpropagation Training. Neural Processing Letters 24(1): 81-92 (2006)
	2005
27		Joshua E. Menke, Tony R. Martinez: Domain expert approximation through oracle learning. ESANN 2005: 205-210
	2004
26		Tony R. Martinez: Neural Networks and Machine Learning: Towards Fully Automated Learning. ENC 2004: 5
25		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)
	2003
24		D. Randall Wilson, Tony R. Martinez: The general inefficiency of batch training for gradient descent learning. Neural Networks 16(10): 1429-1451 (2003)
	2002
23		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
22		Timothy L. Andersen, Tony R. Martinez: DMP3: A Dynamic Multilayer Perceptron Construction Algorithm. Int. J. Neural Syst. 11(2): 145-165 (2001)
21		Xinchuan Zeng, Tony R. Martinez: An algorithm for correcting mislabeled data. Intell. Data Anal. 5(6): 491-502 (2001)
	2000
20		D. Randall Wilson, Tony R. Martinez: The Inefficiency of Batch Training for Large Training Sets. IJCNN (2) 2000: 113-117
19		Xinchuan Zeng, Tony R. Martinez: Rescaling the Energy Function in Hopfield Networks. IJCNN (6) 2000: 498-504
18		D. Randall Wilson, Tony R. Martinez: An Integrated Instance-Based Learning Algorithm. Computational Intelligence 16(1): 1-28 (2000)
17		Dan Ventura, Tony R. Martinez: Quantum associative memory. Inf. Sci. 124(1-4): 273-296 (2000)
16		Xinchuan Zeng, Tony R. Martinez: Distribution-balanced stratified cross-validation for accuracy estimation. J. Exp. Theor. Artif. Intell. 12(1): 1-12 (2000)
15		D. Randall Wilson, Tony R. Martinez: Reduction Techniques for Instance-Based Learning Algorithms. Machine Learning 38(3): 257-286 (2000)
14		Xinchuan Zeng, Tony R. Martinez: Using a Neural Network to Approximate an Ensemble of Classifiers. Neural Processing Letters 12(3): 225-237 (2000)
	1999
13		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
12		D. Randall Wilson, Tony R. Martinez: Instance Pruning Techniques. ICML 1997: 403-411
11		D. Randall Wilson, Tony R. Martinez: Improved Heterogeneous Distance Functions CoRR cs.AI/9701101: (1997)
10		D. Randall Wilson, Tony R. Martinez: Improved Heterogeneous Distance Functions. J. Artif. Intell. Res. (JAIR) 6: 1-34 (1997)
	1996
9		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
8		Christophe G. Giraud-Carrier, Tony R. Martinez: An Integrated Framework for Learning and Reasoning CoRR abs/cs/9508102: (1995)
7		Christophe G. Giraud-Carrier, Tony R. Martinez: An Integrated Framework for Learning and Reasoning. J. Artif. Intell. Res. (JAIR) 3: 147-185 (1995)
6		Christophe G. Giraud-Carrier, Tony R. Martinez: Analysis of the Convergence and Generalization of AA1. J. Parallel Distrib. Comput. 26(1): 125-131 (1995)
	1994
5		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)
4		Kevin S. Van Horn, Tony R. Martinez: The minimum feature set problem. Neural Networks 7(3): 491-494 (1994)
	1991
3		Tony R. Martinez, Douglas M. Campbell: A Self-Adjusting Dynamic Logic Module. J. Parallel Distrib. Comput. 11(4): 303-313 (1991)
	1990
2		Tony R. Martinez: Smart Memory: the Memory Processor Model. Modelling the Innovation 1990: 481-488
	1988
1		Tony R. Martinez, Jacques J. Vidal: Adaptive Parallel Logic Networks. J. Parallel Distrib. Comput. 5(1): 26-58 (1988)

Coauthor Index

1	Timothy L. Andersen	[22]
2	J. C. Barker	[5]
3	Douglas M. Campbell	[3]
4	James L. Carroll	[44]
5	Michael Gashler	[31] [33] [41] [45] [46] [47]
6	Christophe G. Giraud-Carrier	[6] [7] [8] [30] [33]
7	Kevin S. Van Horn	[4]
8	Ernest Istook	[23]
9	Joshua E. Menke	[27] [32] [35] [36]
10	Kristine Monteith	[38] [44]
11	Brent D. Morring	[25]
12	Adam H. Peterson	[34] [37] [42]
13	Michael Rimer	[28] [29]
14	George L. Rudolph	[9] [39] [40] [42]
15	Kevin D. Seppi	[44]
16	Michael R. Smith	[43]
17	Dan Ventura	[17] [31] [41]
18	Jacques J. Vidal	[1]
19	Spencer K. White	[39] [40]
20	D. Randall Wilson	[10] [11] [12] [15] [18] [20] [24]
21	Xinchuan Zeng	[13] [14] [16] [19] [21]

Colors in the list of coauthors

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