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Tony R. Martinez
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2020 – today
- 2024
- [c62]Fanqing Lin, Tony R. Martinez:
Ego2HandsPose: A Dataset for Egocentric Two-hand 3D Global Pose Estimation. WACV 2024: 4363-4371 - 2022
- [c61]Fanqing Lin, Brian L. Price, Tony R. Martinez:
Generalizing Interactive Backpropagating Refinement for Dense Prediction Networks. CVPR 2022: 763-772 - [i20]Fanqing Lin, Tony R. Martinez:
Ego2HandsPose: A Dataset for Egocentric Two-hand 3D Global Pose Estimation. CoRR abs/2206.04927 (2022) - 2021
- [c60]Fanqing Lin, Connor Wilhelm, Tony R. Martinez:
Two-hand Global 3D Pose Estimation using Monocular RGB. WACV 2021: 2372-2380 - [i19]Fanqing Lin, Brian L. Price, Tony R. Martinez:
Generalizing Interactive Backpropagating Refinement for Dense Prediction. CoRR abs/2112.10969 (2021) - 2020
- [j44]Fanqing Lin, Yao Chou, Tony R. Martinez:
Flow Adaptive Video Object Segmentation. Image Vis. Comput. 94: 103864 (2020) - [j43]Chris Tensmeyer
, Tony R. Martinez:
Historical Document Image Binarization: A Review. SN Comput. Sci. 1(3): 173 (2020) - [c59]Mike Brodie, Brian Rasmussen, Chris Tensmeyer, Scott Corbitt, Tony R. Martinez:
CoachGAN. WACV 2020: 3472-3481 - [i18]Fanqing Lin, Connor Wilhelm, Tony R. Martinez:
Two-hand Global 3D Pose Estimation Using Monocular RGB. CoRR abs/2006.01320 (2020) - [i17]Fanqing Lin, Tony R. Martinez:
Ego2Hands: A Dataset for Egocentric Two-hand Segmentation and Detection. CoRR abs/2011.07252 (2020)
2010 – 2019
- 2019
- [j42]Chris Tensmeyer
CONFIRM - Clustering of noisy form images using robust matching. Pattern Recognit. 87: 1-16 (2019) - [c58]Christopher Tensmeyer, Tony R. Martinez:
Robust Keypoint Detection. WML@ICDAR 2019: 1-7 - [c57]Chris Tensmeyer, Vlad I. Morariu, Brian L. Price, Scott Cohen, Tony R. Martinez:
Deep Splitting and Merging for Table Structure Decomposition. ICDAR 2019: 114-121 - [c56]Chris Tensmeyer, Mike Brodie, Daniel Saunders, Tony R. Martinez:
Generating Realistic Binarization Data with Generative Adversarial Networks. ICDAR 2019: 172-177 - 2018
- [j41]Michael R. Smith, Tony R. Martinez:
The robustness of majority voting compared to filtering misclassified instances in supervised classification tasks. Artif. Intell. Rev. 49(1): 105-130 (2018) - [c55]Christopher Tensmeyer, Curtis Wigington, Brian L. Davis, Seth Stewart, Tony R. Martinez, William Barrett:
Language Model Supervision for Handwriting Recognition Model Adaptation. ICFHR 2018: 133-138 - [c54]Mike Brodie, Chris Tensmeyer, Wes Ackerman, Tony R. Martinez:
Alpha Model Domination in Multiple Choice Learning. ICMLA 2018: 879-884 - [i16]Chris Tensmeyer, Curtis Wigington, Brian L. Davis, Seth Stewart, Tony R. Martinez, William Barrett:
Language Model Supervision for Handwriting Recognition Model Adaptation. CoRR abs/1808.01423 (2018) - 2017
- [c53]Chris Tensmeyer, Tony R. Martinez:
Document Image Binarization with Fully Convolutional Neural Networks. ICDAR 2017: 99-104 - [c52]Chris Tensmeyer, Tony R. Martinez:
Analysis of Convolutional Neural Networks for Document Image Classification. ICDAR 2017: 388-393 - [c51]Chris Tensmeyer, Daniel Saunders, Tony R. Martinez:
Convolutional Neural Networks for Font Classification. ICDAR 2017: 985-990 - [c50]Taetem Simms, Clayton Ramstedt, Megan Rich, Michael Richards, Tony R. Martinez, Christophe G. Giraud-Carrier:
Detecting Cognitive Distortions Through Machine Learning Text Analytics. ICHI 2017: 508-512 - [i15]Chris Tensmeyer, Tony R. Martinez:
Analysis of Convolutional Neural Networks for Document Image Classification. CoRR abs/1708.03273 (2017) - [i14]Chris Tensmeyer, Tony R. Martinez:
Document Image Binarization with Fully Convolutional Neural Networks. CoRR abs/1708.03276 (2017) - [i13]Chris Tensmeyer, Daniel Saunders, Tony R. Martinez:
Convolutional Neural Networks for Font Classification. CoRR abs/1708.03669 (2017) - 2016
- [j40]Michael R. Smith, Tony R. Martinez:
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting in Supervised Classification Problems. Comput. Intell. 32(2): 167-195 (2016) - [j39]Michael S. Gashler, Michael R. Smith, Richard G. Morris, Tony R. Martinez:
Missing Value Imputation with Unsupervised Backpropagation. Comput. Intell. 32(2): 196-215 (2016) - 2015
- [j38]George L. Rudolph, Tony R. Martinez:
Finding the Real Differences Between Learning Algorithms. Int. J. Artif. Intell. Tools 24(3): 1550001:1-1550001:20 (2015) - [c49]Michael R. Smith, Michael S. Gashler, Tony R. Martinez:
A hybrid latent variable neural network model for item recommendation. IJCNN 2015: 1-7 - [c48]Michael R. Smith, Tony R. Martinez:
Using Classifier diversity to handle label noise. IJCNN 2015: 1-8 - [c47]Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier:
The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization. MetaSel@PKDD/ECML 2015: 3-14 - 2014
- [j37]Michael R. Smith
An instance level analysis of data complexity. Mach. Learn. 95(2): 225-256 (2014) - [c46]Michael R. Smith, Logan Mitchell, Christophe G. Giraud-Carrier, Tony R. Martinez:
Recommending Learning Algorithms and Their Associated Hyperparameters. MetaSel@ECAI 2014: 39-40 - [c45]Michael R. Smith, Andrew White, Christophe G. Giraud-Carrier, Tony R. Martinez:
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. MetaSel@ECAI 2014: 41-48 - [c44]Michael R. Smith, Tony R. Martinez:
Reducing the Effects of Detrimental Instances. ICMLA 2014: 183-188 - [i12]Michael R. Smith, Tony R. Martinez:
Becoming More Robust to Label Noise with Classifier Diversity. CoRR abs/1403.1893 (2014) - [i11]Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier:
The Potential Benefits of Filtering Versus Hyper-Parameter Optimization. CoRR abs/1403.3342 (2014) - [i10]Michael R. Smith, Andrew White, Christophe G. Giraud-Carrier, Tony R. Martinez:
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. CoRR abs/1405.7292 (2014) - [i9]Michael R. Smith, Tony R. Martinez, Michael Gashler:
A Hybrid Latent Variable Neural Network Model for Item Recommendation. CoRR abs/1406.2235 (2014) - [i8]Michael R. Smith, Tony R. Martinez:
Reducing the Effects of Detrimental Instances. CoRR abs/1406.2237 (2014) - [i7]Michael R. Smith, Logan Mitchell, Christophe G. Giraud-Carrier, Tony R. Martinez:
Recommending Learning Algorithms and Their Associated Hyperparameters. CoRR abs/1407.1890 (2014) - [i6]Richard G. Morris, Tony R. Martinez, Michael R. Smith:
A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning. CoRR abs/1410.4777 (2014) - 2013
- [j36]Kristine Monteith, Tony R. Martinez:
Aggregate Certainty estimators. Comput. Intell. 29(2): 207-232 (2013) - [c43]Kristine Monteith, Bruce Brown, Dan Ventura, Tony R. Martinez:
Automatic Generation of Music for Inducing Physiological Response. CogSci 2013 - [i5]Michael R. Smith, Tony R. Martinez:
An Extensive Evaluation of Filtering Misclassified Instances in Supervised Classification Tasks. CoRR abs/1312.3970 (2013) - [i4]Michael R. Smith, Tony R. Martinez:
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting. CoRR abs/1312.4986 (2013) - [i3]Michael Gashler, Michael R. Smith, Richard G. Morris, Tony R. Martinez:
Missing Value Imputation With Unsupervised Backpropagation. CoRR abs/1312.5394 (2013) - 2012
- [j35]Spencer K. White, Tony R. Martinez, George L. Rudolph:
Automatic Algorithm Development Using New Reinforcement Programming Techniques. Comput. Intell. 28(2): 176-208 (2012) - [j34]Michael Gashler, Tony R. Martinez:
Robust manifold learning with CycleCut. Connect. Sci. 24(1): 57-69 (2012) - [c42]Kristine Monteith, Tony R. Martinez, Dan Ventura:
Automatic Generation of Melodic Accompaniments for Lyrics. ICCC 2012: 87-94 - 2011
- [j33]Michael Gashler, Dan Ventura, Tony R. Martinez:
Manifold Learning by Graduated Optimization. IEEE Trans. Syst. Man Cybern. Part B 41(6): 1458-1470 (2011) - [c41]Kristine Monteith, Virginia Francisco, Tony R. Martinez, Pablo Gervás, Dan Ventura:
Automatic Generation of Emotionally-Targeted Soundtracks. ICCC 2011: 60-62 - [c40]Adam H. Peterson, Tony R. Martinez, George L. Rudolph:
On the structure of algorithm spaces. IJCNN 2011: 658-665 - [c39]Michael Gashler, Tony R. Martinez:
Temporal nonlinear dimensionality reduction. IJCNN 2011: 1959-1966 - [c38]Michael Gashler, Tony R. Martinez:
Tangent space guided intelligent neighbor finding. IJCNN 2011: 2617-2624 - [c37]Kristine Monteith, James L. Carroll, Kevin D. Seppi, Tony R. Martinez:
Turning Bayesian model averaging into Bayesian model combination. IJCNN 2011: 2657-2663 - [c36]Michael R. Smith, Tony R. Martinez:
Improving classification accuracy by identifying and removing instances that should be misclassified. IJCNN 2011: 2690-2697 - 2010
- [j32]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) - [c35]Spencer K. White, Tony R. Martinez, George L. Rudolph:
Generating three binary addition algorithms using reinforcement programming. ACM Southeast Regional Conference 2010: 46 - [c34]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 - [c33]Kristine Monteith, Tony R. Martinez, Dan Ventura:
Automatic Generation of Music for Inducing Emotive Response. ICCC 2010: 140-149 - [c32]Kristine Monteith, Tony R. Martinez:
Using multiple measures to predict confidence in instance classification. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j31]Joshua E. Menke, Tony R. Martinez:
Artificial neural network reduction through oracle learning. Intell. Data Anal. 13(1): 135-149 (2009) - [j30]Adam H. Peterson, Tony R. Martinez:
Reducing Decision Tree Ensemble Size Using Parallel Decision DAGs. Int. J. Artif. Intell. Tools 18(4): 613-620 (2009) - [j29]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
- [j28]Joshua E. Menke, Tony R. Martinez:
A Bradley-Terry artificial neural network model for individual ratings in group competitions. Neural Comput. Appl. 17(2): 175-186 (2008) - [c31]Michael Gashler, Christophe G. Giraud-Carrier, Tony R. Martinez:
Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous. ICMLA 2008: 900-905 - 2007
- [j27]Christophe G. Giraud-Carrier, Tony R. Martinez:
Learning by Discrimination: A Constructive Incremental Approach. J. Comput. 2(7): 49-58 (2007) - [c30]Michael Gashler, Dan Ventura, Tony R. Martinez:
Iterative Non-linear Dimensionality Reduction with Manifold Sculpting. NIPS 2007: 513-520 - 2006
- [j26]Michael Rimer, Tony R. Martinez:
Classification-based objective functions. Mach. Learn. 63(2): 183-205 (2006) - [j25]Michael Rimer, Tony R. Martinez:
CB3: An Adaptive Error Function for Backpropagation Training. Neural Process. Lett. 24(1): 81-92 (2006) - 2005
- [c29]Joshua E. Menke, Tony R. Martinez:
Domain expert approximation through oracle learning. ESANN 2005: 205-210 - 2004
- [j24]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) - [c28]Tony R. Martinez:
Neural Networks and Machine Learning: Towards Fully Automated Learning. ENC 2004: 5 - [c27]Michael Rimer, Tony R. Martinez:
Softprop: softmax neural network backpropagation learning. IJCNN 2004: 979-983 - [c26]Xinchuan Zeng, Tony R. Martinez:
Feature weighting using neural networks. IJCNN 2004: 1327-1330 - [c25]Joshua E. Menke, Tony R. Martinez:
Using permutations instead of student's t distribution for p-values in paired-difference algorithm comparisons. IJCNN 2004: 1331-1335 - 2003
- [j23]D. Randall Wilson, Tony R. Martinez:
The general inefficiency of batch training for gradient descent learning. Neural Networks 16(10): 1429-1451 (2003) - 2002
- [j22]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
- [j21]Xinchuan Zeng, Tony R. Martinez:
An algorithm for correcting mislabeled data. Intell. Data Anal. 5(6): 491-502 (2001) - [j20]Timothy L. Andersen, Tony R. Martinez:
DMP3: A Dynamic Multilayer Perceptron Construction Algorithm. Int. J. Neural Syst. 11(2): 145-165 (2001) - 2000
- [j19]D. Randall Wilson, Tony R. Martinez:
An Integrated Instance-Based Learning Algorithm. Comput. Intell. 16(1): 1-28 (2000) - [j18]Dan Ventura, Tony R. Martinez:
Quantum associative memory. Inf. Sci. 124(1-4): 273-296 (2000) - [j17]Xinchuan Zeng, Tony R. Martinez:
Distribution-balanced stratified cross-validation for accuracy estimation. J. Exp. Theor. Artif. Intell. 12(1): 1-12 (2000) - [j16]D. Randall Wilson, Tony R. Martinez:
Reduction Techniques for Instance-Based Learning Algorithms. Mach. Learn. 38(3): 257-286 (2000) - [j15]Xinchuan Zeng, Tony R. Martinez:
Using a Neural Network to Approximate an Ensemble of Classifiers. Neural Process. Lett. 12(3): 225-237 (2000) - [c24]D. Randall Wilson, Tony R. Martinez:
The Inefficiency of Batch Training for Large Training Sets. IJCNN (2) 2000: 113-117 - [c23]Xinchuan Zeng, Tony R. Martinez:
Rescaling the Energy Function in Hopfield Networks. IJCNN (6) 2000: 498-504
1990 – 1999
- 1999
- [j14]Xinchuan Zeng, Tony R. Martinez:
A New Relaxation Procedure in the Hopfield Network for Solving Optimization Problems. Neural Process. Lett. 10(3): 211-222 (1999) - [c22]Dan Ventura, Tony R. Martinez:
A Quantum Associative Memory Based on Grover's Algorithm. ICANNGA 1999: 22-27 - [c21]Xinchuan Zeng, Tony R. Martinez:
Improving the Performance of the Hopfield Network By Using A Relaxation Rate. ICANNGA 1999: 67-72 - [c20]Xinchuan Zeng, Tony R. Martinez:
A New Activation Function in the Hopfield Network for Solving Optimization Problems. ICANNGA 1999: 73-77 - [c19]Xinchuan Zeng, Tony R. Martinez:
Extending the power and capacity of constraint satisfaction networks. IJCNN 1999: 432-437 - [c18]D. Randall Wilson, Dan Ventura, Brian Moncur, Tony R. Martinez:
The robustness of relaxation rates in constraint satisfaction networks. IJCNN 1999: 650-654 - [c17]D. Randall Wilson, Tony R. Martinez:
Combining cross-validation and confidence to measure fitness. IJCNN 1999: 1409-1414 - [c16]Tim Andersen, Tony R. Martinez:
The little neuron that could. IJCNN 1999: 1608-1613 - [c15]Tim Andersen, Tony R. Martinez:
Cross validation and MLP architecture selection. IJCNN 1999: 1614-1619 - [c14]Dan Ventura, D. Randall Wilson, Brian Moncur, Tony R. Martinez:
A neural model of centered tri-gram speech recognition. IJCNN 1999: 3050-3053 - 1997
- [j13]George L. Rudolph, Tony R. Martinez:
A transformation strategy for implementing distributed, multilayer feedforward neural networks: Backpropagation transformation. Future Gener. Comput. Syst. 12(6): 547-564 (1997) - [j12]D. Randall Wilson, Tony R. Martinez:
Improved Heterogeneous Distance Functions. J. Artif. Intell. Res. 6: 1-34 (1997) - [c13]Dan Ventura, Tony R. Martinez:
An Artificial Neuron with Quantum Mechanical Properties. ICANNGA 1997: 482-485 - [c12]D. Randall Wilson, Tony R. Martinez:
Improved Center Point Selection for Probabilistic Neural Networks. ICANNGA 1997: 514-517 - [c11]D. Randall Wilson, Tony R. Martinez:
Instance Pruning Techniques. ICML 1997: 403-411 - [i2]D. Randall Wilson, Tony R. Martinez:
Improved Heterogeneous Distance Functions. CoRR cs.AI/9701101 (1997) - 1996
- [j11]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) - [c10]Dan Ventura, Tony R. Martinez:
Robust optimization using training set evolution. ICNN 1996: 524-528 - [c9]D. Randall Wilson, Tony R. Martinez:
Heterogeneous radial basis function networks. ICNN 1996: 1263-1267 - 1995
- [j10]Christophe G. Giraud-Carrier, Tony R. Martinez:
An Integrated Framework for Learning and Reasoning. J. Artif. Intell. Res. 3: 147-185 (1995) - [j9]Christophe G. Giraud-Carrier, Tony R. Martinez:
Analysis of the Convergence and Generalization of AA1. J. Parallel Distributed Comput. 26(1): 125-131 (1995) - [j8]George L. Rudolph, Tony R. Martinez:
A transformation for implementing localist neural networks. Neural Parallel Sci. Comput. 3(2): 173-187 (1995) - [c8]George L. Rudolph, Tony R. Martinez:
A Transformation for Implementing Efficient Dynamic Backpropagation Neural Networks. ICANNGA 1995: 41-44 - [c7]Christophe G. Giraud-Carrier, Tony R. Martinez:
AA1*: A Dynamic Incremental Network that Learns by Discrimination. ICANNGA 1995: 45-48 - [c6]Dan Ventura, Tim Andersen, Tony R. Martinez:
Using Evolutionary Computation to Generate Training Set Data for Neural Networks. ICANNGA 1995: 468-471 - [i1]Christophe G. Giraud-Carrier, Tony R. Martinez:
An Integrated Framework for Learning and Reasoning. CoRR abs/cs/9508102 (1995) - 1994
- [j7]George L. Rudolph, Tony R. Martinez:
Location-Independent Transformations: a General Strategy for Implementing Neural Networks. Int. J. Artif. Intell. Tools 3(3): 417-428 (1994) - [j6]Kevin S. Van Horn, Tony R. Martinez:
The minimum feature set problem. Neural Networks 7(3): 491-494 (1994) - [j5]J. C. Barker, Tony R. Martinez:
Proof of correctness for ASOCS AA3 networks. IEEE Trans. Syst. Man Cybern. 24(3): 503-510 (1994) - [c5]Matthew G. Stout, Linton G. Salmon, George L. Rudolph, Tony R. Martinez:
A VLSI implementation of a parallel, self-organizing learning model. ICPR (3) 1994: 373-376 - 1993
- [c4]Christophe G. Giraud-Carrier, Tony R. Martinez:
Using precepts to augment training set learning. ANNES 1993: 46-51 - [c3]D. Randall Wilson, Tony R. Martinez:
The importance of using multiple styles of generalization. ANNES 1993: 54-57 - [c2]Tony R. Martinez, Brent W. Hughes:
Towards a general distributed platform for learning and generalization. ANNES 1993: 216-219 - 1991
- [j4]Tony R. Martinez, Douglas M. Campbell:
A Self-Adjusting Dynamic Logic Module. J. Parallel Distributed Comput. 11(4): 303-313 (1991) - [j3]Tony R. Martinez, Douglas M. Campbell:
A self-organizing binary decision tree for incrementally defined rule-based systems. IEEE Trans. Syst. Man Cybern. 21(5): 1231-1238 (1991) - 1990
- [j2]Tony R. Martinez:
Smart memory architecture and methods. Future Gener. Comput. Syst. 6(2): 145-162 (1990) - [c1]Tony R. Martinez:
Smart Memory: the Memory Processor Model. Modelling the Innovation 1990: 481-488
1980 – 1989
- 1988
- [j1]Tony R. Martinez, Jacques J. Vidal:
Adaptive Parallel Logic Networks. J. Parallel Distributed Comput. 5(1): 26-58 (1988)
Coauthor Index
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