Adaptive Parallel Logic Networks. - Tony R. Martinez; Jacques J. Vidal (J. Parallel Distributed Comput., 1988)

Smart Memory: the Memory Processor Model. - Tony R. Martinez (Modelling the Innovation, 1990)

Smart memory architecture and methods. - Tony R. Martinez (Future Gener. Comput. Syst., 1990)

A Self-Adjusting Dynamic Logic Module. - Tony R. Martinez; Douglas M. Campbell (J. Parallel Distributed Comput., 1991)

A self-organizing binary decision tree for incrementally defined rule-based systems. - Tony R. Martinez; Douglas M. Campbell (IEEE Trans. Syst. Man Cybern., 1991)

Using precepts to augment training set learning. - Christophe G. Giraud-Carrier; Tony R. Martinez (ANNES, 1993)

Towards a general distributed platform for learning and generalization. - Tony R. Martinez; Brent W. Hughes (ANNES, 1993)

The importance of using multiple styles of generalization. - D. Randall Wilson; Tony R. Martinez (ANNES, 1993)

A VLSI implementation of a parallel, self-organizing learning model. - Matthew G. Stout; Linton G. Salmon; George L. Rudolph; Tony R. Martinez (ICPR (3), 1994)

Location-Independent Transformations: a General Strategy for Implementing Neural Networks. - George L. Rudolph; Tony R. Martinez (Int. J. Artif. Intell. Tools, 1994)

The minimum feature set problem. - Kevin S. Van Horn; Tony R. Martinez (Neural Networks, 1994)

Proof of correctness for ASOCS AA3 networks. - J. C. Barker; Tony R. Martinez (IEEE Trans. Syst. Man Cybern., 1994)

AA1*: A Dynamic Incremental Network that Learns by Discrimination. - Christophe G. Giraud-Carrier; Tony R. Martinez (ICANNGA, 1995)

A Transformation for Implementing Efficient Dynamic Backpropagation Neural Networks. - George L. Rudolph; Tony R. Martinez (ICANNGA, 1995)

Using Evolutionary Computation to Generate Training Set Data for Neural Networks. - Dan Ventura; Tim Andersen; Tony R. Martinez (ICANNGA, 1995)

An Integrated Framework for Learning and Reasoning. - Christophe G. Giraud-Carrier; Tony R. Martinez (J. Artif. Intell. Res., 1995)

Analysis of the Convergence and Generalization of AA1. - Christophe G. Giraud-Carrier; Tony R. Martinez (J. Parallel Distributed Comput., 1995)

A transformation for implementing localist neural networks. - George L. Rudolph; Tony R. Martinez (Neural Parallel Sci. Comput., 1995)

Robust optimization using training set evolution. - Dan Ventura; Tony R. Martinez (ICNN, 1996)

Heterogeneous radial basis function networks. - D. Randall Wilson; Tony R. Martinez (ICNN, 1996)

LIA: A Location-Independent Transformation for ASOCS Adaptive Algorithm 2. - George L. Rudolph; Tony R. Martinez (Int. J. Neural Syst., 1996)

An Artificial Neuron with Quantum Mechanical Properties. - Dan Ventura; Tony R. Martinez (ICANNGA, 1997)

Improved Center Point Selection for Probabilistic Neural Networks. - D. Randall Wilson; Tony R. Martinez (ICANNGA, 1997)

Instance Pruning Techniques. - D. Randall Wilson; Tony R. Martinez (ICML, 1997)

A transformation strategy for implementing distributed, multilayer feedforward neural networks: Backpropagation transformation. - George L. Rudolph; Tony R. Martinez (Future Gener. Comput. Syst., 1997)

Improved Heterogeneous Distance Functions. - D. Randall Wilson; Tony R. Martinez (J. Artif. Intell. Res., 1997)

A Quantum Associative Memory Based on Grover's Algorithm. - Dan Ventura; Tony R. Martinez (ICANNGA, 1999)

Improving the Performance of the Hopfield Network By Using A Relaxation Rate. - Xinchuan Zeng; Tony R. Martinez (ICANNGA, 1999)

A New Activation Function in the Hopfield Network for Solving Optimization Problems. - Xinchuan Zeng; Tony R. Martinez (ICANNGA, 1999)

The little neuron that could. - Tim Andersen; Tony R. Martinez (IJCNN, 1999)

Cross validation and MLP architecture selection. - Tim Andersen; Tony R. Martinez (IJCNN, 1999)

A neural model of centered tri-gram speech recognition. - Dan Ventura; D. Randall Wilson; Brian Moncur; Tony R. Martinez (IJCNN, 1999)

Combining cross-validation and confidence to measure fitness. - D. Randall Wilson; Tony R. Martinez (IJCNN, 1999)

The robustness of relaxation rates in constraint satisfaction networks. - D. Randall Wilson; Dan Ventura; Brian Moncur; Tony R. Martinez (IJCNN, 1999)

Extending the power and capacity of constraint satisfaction networks. - Xinchuan Zeng; Tony R. Martinez (IJCNN, 1999)

A New Relaxation Procedure in the Hopfield Network for Solving Optimization Problems. - Xinchuan Zeng; Tony R. Martinez (Neural Process. Lett., 1999)

The Inefficiency of Batch Training for Large Training Sets. - D. Randall Wilson; Tony R. Martinez (IJCNN (2), 2000)

Rescaling the Energy Function in Hopfield Networks. - Xinchuan Zeng; Tony R. Martinez (IJCNN (6), 2000)

An Integrated Instance-Based Learning Algorithm. - D. Randall Wilson; Tony R. Martinez (Comput. Intell., 2000)

Quantum associative memory. - Dan Ventura; Tony R. Martinez (Inf. Sci., 2000)

Distribution-balanced stratified cross-validation for accuracy estimation. - Xinchuan Zeng; Tony R. Martinez (J. Exp. Theor. Artif. Intell., 2000)

Reduction Techniques for Instance-Based Learning Algorithms. - D. Randall Wilson; Tony R. Martinez (Mach. Learn., 2000)

Using a Neural Network to Approximate an Ensemble of Classifiers. - Xinchuan Zeng; Tony R. Martinez (Neural Process. Lett., 2000)

An algorithm for correcting mislabeled data. - Xinchuan Zeng; Tony R. Martinez (Intell. Data Anal., 2001)

DMP3: A Dynamic Multilayer Perceptron Construction Algorithm. - Timothy L. Andersen; Tony R. Martinez (Int. J. Neural Syst., 2001)

Improved Backpropagation Learning in Neural Networks with Windowed Momentum. - Ernest Istook; Tony R. Martinez (Int. J. Neural Syst., 2002)

The general inefficiency of batch training for gradient descent learning. - D. Randall Wilson; Tony R. Martinez (Neural Networks, 2003)

Neural Networks and Machine Learning: Towards Fully Automated Learning. - Tony R. Martinez (ENC, 2004)

Using permutations instead of student's t distribution for p-values in paired-difference algorithm comparisons. - Joshua E. Menke; Tony R. Martinez (IJCNN, 2004)

Softprop: softmax neural network backpropagation learning. - Michael Rimer; Tony R. Martinez (IJCNN, 2004)

Feature weighting using neural networks. - Xinchuan Zeng; Tony R. Martinez (IJCNN, 2004)

Weighted Instance Typicality Search (WITS): A nearest neighbor data reduction algorithm. - Brent D. Morring; Tony R. Martinez (Intell. Data Anal., 2004)

Domain expert approximation through oracle learning. - Joshua E. Menke; Tony R. Martinez (ESANN, 2005)

Classification-based objective functions. - Michael Rimer; Tony R. Martinez (Mach. Learn., 2006)

CB3: An Adaptive Error Function for Backpropagation Training. - Michael Rimer; Tony R. Martinez (Neural Process. Lett., 2006)

Iterative Non-linear Dimensionality Reduction with Manifold Sculpting. - Michael Gashler; Dan Ventura; Tony R. Martinez (NIPS, 2007)

Learning by Discrimination: A Constructive Incremental Approach. - Christophe G. Giraud-Carrier; Tony R. Martinez (J. Comput., 2007)

Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous. - Michael Gashler; Christophe G. Giraud-Carrier; Tony R. Martinez (ICMLA, 2008)

A Bradley-Terry artificial neural network model for individual ratings in group competitions. - Joshua E. Menke; Tony R. Martinez (Neural Comput. Appl., 2008)

Artificial neural network reduction through oracle learning. - Joshua E. Menke; Tony R. Martinez (Intell. Data Anal., 2009)

Reducing Decision Tree Ensemble Size Using Parallel Decision DAGs. - Adam H. Peterson; Tony R. Martinez (Int. J. Artif. Intell. Tools, 2009)

Improving Supervised Learning by Adapting the Problem to the Learner. - Joshua E. Menke; Tony R. Martinez (Int. J. Neural Syst., 2009)

Generating three binary addition algorithms using reinforcement programming. - Spencer K. White; Tony R. Martinez; George L. Rudolph (ACM Southeast Regional Conference, 2010)

Generating a novel sort algorithm using Reinforcement Programming. - Spencer K. White; Tony R. Martinez; George L. Rudolph (IEEE Congress on Evolutionary Computation, 2010)

Automatic Generation of Music for Inducing Emotive Response. - Kristine Monteith; Tony R. Martinez; Dan Ventura (ICCC, 2010)

Using multiple measures to predict confidence in instance classification. - Kristine Monteith; Tony R. Martinez (IJCNN, 2010)

Using learning algorithm behavior to chart task space: The DICES distance. - Adam H. Peterson; Tony R. Martinez (Intell. Data Anal., 2010)

Automatic Generation of Emotionally-Targeted Soundtracks. - Kristine Monteith; Virginia Francisco; Tony R. Martinez; Pablo Gervás; Dan Ventura (ICCC, 2011)

Temporal nonlinear dimensionality reduction. - Michael Gashler; Tony R. Martinez (IJCNN, 2011)

Tangent space guided intelligent neighbor finding. - Michael Gashler; Tony R. Martinez (IJCNN, 2011)

Turning Bayesian model averaging into Bayesian model combination. - Kristine Monteith; James L. Carroll; Kevin D. Seppi; Tony R. Martinez (IJCNN, 2011)

On the structure of algorithm spaces. - Adam H. Peterson; Tony R. Martinez; George L. Rudolph (IJCNN, 2011)

Improving classification accuracy by identifying and removing instances that should be misclassified. - Michael R. Smith 002; Tony R. Martinez (IJCNN, 2011)

Manifold Learning by Graduated Optimization. - Michael Gashler; Dan Ventura; Tony R. Martinez (IEEE Trans. Syst. Man Cybern. Part B, 2011)

Automatic Generation of Melodic Accompaniments for Lyrics. - Kristine Monteith; Tony R. Martinez; Dan Ventura (ICCC, 2012)

Automatic Algorithm Development Using New Reinforcement Programming Techniques. - Spencer K. White; Tony R. Martinez; George L. Rudolph (Comput. Intell., 2012)

Robust manifold learning with CycleCut. - Michael Gashler; Tony R. Martinez (Connect. Sci., 2012)

Automatic Generation of Music for Inducing Physiological Response. - Kristine Monteith; Bruce Brown; Dan Ventura; Tony R. Martinez (CogSci, 2013)

Aggregate Certainty estimators. - Kristine Monteith; Tony R. Martinez (Comput. Intell., 2013)

An Extensive Evaluation of Filtering Misclassified Instances in Supervised Classification Tasks. - Michael R. Smith 002; Tony R. Martinez (CoRR, 2013)

A Comparative Evaluation of Curriculum Learning with Filtering and Boosting. - Michael R. Smith 002; Tony R. Martinez (CoRR, 2013)

Recommending Learning Algorithms and Their Associated Hyperparameters. - Michael R. Smith 002; Logan Mitchell; Christophe G. Giraud-Carrier; Tony R. Martinez (MetaSel@ECAI, 2014)

An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage. - Michael R. Smith 002; Andrew White; Christophe G. Giraud-Carrier; Tony R. Martinez (MetaSel@ECAI, 2014)

Reducing the Effects of Detrimental Instances. - Michael R. Smith 002; Tony R. Martinez (ICMLA, 2014)

A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning. - Richard G. Morris; Tony R. Martinez; Michael R. Smith 002 (CoRR, 2014)

Becoming More Robust to Label Noise with Classifier Diversity. - Michael R. Smith 002; Tony R. Martinez (CoRR, 2014)

The Potential Benefits of Filtering Versus Hyper-Parameter Optimization. - Michael R. Smith 002; Tony R. Martinez; Christophe G. Giraud-Carrier (CoRR, 2014)

An instance level analysis of data complexity. - Michael R. Smith 002; Tony R. Martinez; Christophe G. Giraud-Carrier (Mach. Learn., 2014)

A hybrid latent variable neural network model for item recommendation. - Michael R. Smith 002; Michael S. Gashler; Tony R. Martinez (IJCNN, 2015)

Using Classifier diversity to handle label noise. - Michael R. Smith 002; Tony R. Martinez (IJCNN, 2015)

The Potential Benefits of Data Set Filtering and Learning Algorithm Hyperparameter Optimization. - Michael R. Smith 002; Tony R. Martinez; Christophe G. Giraud-Carrier (MetaSel@PKDD/ECML, 2015)

Finding the Real Differences Between Learning Algorithms. - George L. Rudolph; Tony R. Martinez (Int. J. Artif. Intell. Tools, 2015)

Missing Value Imputation with Unsupervised Backpropagation. - Michael S. Gashler; Michael R. Smith 002; Richard G. Morris; Tony R. Martinez (Comput. Intell., 2016)

A Comparative Evaluation of Curriculum Learning with Filtering and Boosting in Supervised Classification Problems. - Michael R. Smith 002; Tony R. Martinez (Comput. Intell., 2016)

Document Image Binarization with Fully Convolutional Neural Networks. - Chris Tensmeyer; Tony R. Martinez (ICDAR, 2017)

Analysis of Convolutional Neural Networks for Document Image Classification. - Chris Tensmeyer; Tony R. Martinez (ICDAR, 2017)

Convolutional Neural Networks for Font Classification. - Chris Tensmeyer; Daniel Saunders; Tony R. Martinez (ICDAR, 2017)

Detecting Cognitive Distortions Through Machine Learning Text Analytics. - Taetem Simms; Clayton Ramstedt; Megan Rich; Michael Richards; Tony R. Martinez; Christophe G. Giraud-Carrier (ICHI, 2017)

Language Model Supervision for Handwriting Recognition Model Adaptation. - Christopher Tensmeyer; Curtis Wigington; Brian L. Davis; Seth Stewart; Tony R. Martinez; William Barrett (ICFHR, 2018)

Alpha Model Domination in Multiple Choice Learning. - Mike Brodie; Chris Tensmeyer; Wes Ackerman; Tony R. Martinez (ICMLA, 2018)

The robustness of majority voting compared to filtering misclassified instances in supervised classification tasks. - Michael R. Smith 002; Tony R. Martinez (Artif. Intell. Rev., 2018)

Generating Realistic Binarization Data with Generative Adversarial Networks. - Chris Tensmeyer; Mike Brodie; Daniel Saunders; Tony R. Martinez (ICDAR, 2019)

Robust Keypoint Detection. - Christopher Tensmeyer; Tony R. Martinez (WML@ICDAR, 2019)

Deep Splitting and Merging for Table Structure Decomposition. - Chris Tensmeyer; Vlad I. Morariu; Brian L. Price; Scott Cohen; Tony R. Martinez (ICDAR, 2019)

CONFIRM - Clustering of noisy form images using robust matching. - Chris Tensmeyer; Tony R. Martinez (Pattern Recognit., 2019)

CoachGAN. - Mike Brodie; Brian Rasmussen; Chris Tensmeyer; Scott Corbitt; Tony R. Martinez (WACV, 2020)

Ego2Hands: A Dataset for Egocentric Two-hand Segmentation and Detection. - Fanqing Lin; Tony R. Martinez (CoRR, 2020)

Flow Adaptive Video Object Segmentation. - Fanqing Lin; Yao Chou; Tony R. Martinez (Image Vis. Comput., 2020)

Historical Document Image Binarization: A Review. - Chris Tensmeyer; Tony R. Martinez (SN Comput. Sci., 2020)

Two-hand Global 3D Pose Estimation using Monocular RGB. - Fanqing Lin; Connor Wilhelm; Tony R. Martinez (WACV, 2021)

Generalizing Interactive Backpropagating Refinement for Dense Prediction. - Fanqing Lin; Brian L. Price; Tony R. Martinez (CoRR, 2021)

Generalizing Interactive Backpropagating Refinement for Dense Prediction Networks. - Fanqing Lin; Brian L. Price; Tony R. Martinez (CVPR, 2022)

Ego2HandsPose: A Dataset for Egocentric Two-hand 3D Global Pose Estimation. - Fanqing Lin; Tony R. Martinez (WACV, 2024)