Recent Publications

Journal
  1. Lovinger, J., Valova, I. Infinite Lattice Learner: an ensemble for incremental learning. Soft Comput 24, 6957– 6974 (2020). https://doi.org/10.1007/s00500-019-04330-7
  2. J.Lovinger, I.Valova, C.Clogh, Gist: General Integrated Summarization of Text and Reviews, Journal on Soft Computing, Springer, 23: 1589–1601, issue 5, 2019.
  3. J.Lovinger, I.Valova, Adaptive Predictive System for Survey Analysis: Classification Under Highly Uncertain Conditions, Progress in Artificial Intelligence, Springer, 6: 3, 221-234, 2017.
  4. J.Olson, I.Valova, H.Michel, WSCISOM: Wireless Sensor Data Cluster Identification Through a Hybrid SOM/MLP/RBF Architecture, Progress in Artificial Intelligence, Springer, 4: 5, 233-250, 2016.
  5. D.Avila, I.Valova, RADDACL2: A Recursive Approach to Discovering Density Clusters, Progress in Artificial Intelligence, Springer, 4:1, 21-36, 2015.
  6. C.Gorman, I.Valova, GORMANN: Gravitationally Organized Related Mapping Artificial Neural Network, The Computer Journal, Oxford, July 2015.
  7. C.Gorman, I.Valova, No Neuron Left Behind: A Genetic Approach to Higher Precision Topological Mapping of Self-Organizing Maps, Central European Journal of Computer Science, January 2015.
  8. B. J.Ford, H.Xu, I.Valova, A Real-Time Self-Adaptive Classifier for Identifying Suspicious Bidders in Online Auctions. The Computer Journal, Oxford, Vol. 56, No. 5, 646 – 664, 2013.
Conferences (last 5 years only)
    1. I.Valova, C.Harris, N.Gueorguieva, T.Mai, In-Between Layers Modular Residual Neural Network for the Classification of Images, 7th International Conference of Control, Dynamic Systems, and Robotics, Canada, 2020.
    2. N.Gueorguieva, I.Valova, D.Klusek, Solving Large Scale Classification Problems with Stochastic Based Optimization, Procedia Computer Sciences (Elsevier), Complex Adaptive Systems (CAS), 2019, pp. Vol.168, pp 26-33.
    3. N.Gueorguieva, I.Valova, B.Keegan, Solving Regression Models with First Order Stochastic Based Optimizers, 9th International IEEE EMBS Conference on Neural Engineering, San Francisco, CA, March, 2019.
    4. A.Westgate, I.Valova, A Graph Based Approach to Sentiment Lexicon Expansion, International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Montreal, Canada, June, 2018.
    5. N.Gueorguieva, I.Valova, G.Georgiev, M&MFCM: Fuzzy C-means Clustering with Mahalanobis and Minkowski Distance Metrics, Procedia Computer Science 114C, 2017, pp. 224 – 233.
    6. J.Lovinger, I.Valova, Neural Field: Supervised Apportioned Incremental Learning (SAIL), Proceedings International Joint Conference on Neural Networks (IJCNN), World Congress on Computational Intelligence (WCCI), Vancouver, Canada, 2016.
    7. N.Gueorguieva, I.Valova, G.Georgiev, Fuzzyfication of Principle Component Analysis for Data Dimensionality Reduction, Proceedings IEEE Conference on Fuzzy Systems, World Congress on Computational Intelligence (WCCI), Vancouver, Canada, 2016.
    8. A.Gangopadhyay, J.Rezendes, K.Lyndon, R.Balasubramanian, I.Valova, Toward an Automated Detection of the Gulf Stream North Wall From Concurrent Satellite Images, Proceedings of the Marine Technology Society, MTS/IEEE Oceans’15, 2015.
    9. J.Lovinger, I.Valova, Scrubbing the Web for Association Rules, an Application in Predictive Text, International Conference on Machine Learning and Applications (ICMLA), Miami, Florida, 2015.
    10. C.Rogers, I.Valova, Decaying Potential Fields Neural Network: an Approach for Parallelizing Topologically Indicative Mapping Exemplars, International Conference on Machine Learning and Applications (ICMLA), Miami, Florida, 2015.