Main Page
 Research
 Publications
 Teaching
 The Team
Suleyman Serdar Kozat, PhD
  Associate Professor
  Department of Electrical and Electronics Engineering
  Bilkent University
  Ankara, Turkey 06800

  
 Office: EE-309
 Tel: +90-312-290 2336
 Fax: +90-312-290 1223
 Email:
 

Journal Papers | Journal Papers (Preprints) | Book Chapters | Theses | Conference Papers | Patents  ]

Journal Papers

  1. T. Ergen and S. S. Kozat, ``Online Training of LSTM Networks in Distributed Systems for Variable Length Data Sequences,'' IEEE Transactions on Neural Networks and Learning Systems, Accepted, 2017.
        
  2. K. Gokcesu and S. S. Kozat, ``An Online Minimax Optimal Algorithm for Adversarial Multi-Armed Bandit Problem,'' IEEE Transactions on Neural Networks and Learning Systems, Accepted, 2017.
        
  3. K. Gokcesu and S. S. Kozat, ``Online Anomaly Detection with Minimax Optimal Density Estimation in Nonstationary Environments,'' IEEE Transactions on Signal Processing, Accepted, 2017.
        
  4. T. Ergen and S. S. Kozat, ``Efficient Online Learning Algorithms Based on LSTM Neural Networks,'' IEEE Transactions on Neural Networks and Learning Systems, Accepted, 2017.
        
  5. K. Gokcesu and S. S. Kozat, ``Online Density Estimation of Nonstationary Sources Using Exponential Family of Distributions,'' IEEE Transactions on Neural Networks and Learning Systems, Accepted, 2017.
        
  6. B. C. Civek and S. S. Kozat, ``Efficient Implementation Of Newton-Raphson Methods On Time Series,'' IEEE Transactions on Knowledge and Data Engineering, Accepted, 2017.
        
  7. M. O. Sayin, N. D. Vanli, S. S. Kozat and T. Basar, ``Stochastic Subgradient Algorithms for Strongly Convex Optimization over Distributed Networks,'' IEEE Transactions on Network Science and EngineeringNetwork Science and Engineering, Accepted, 2017.
        
  8. M. O. Sayin, S. S. Kozat and T. Basar, ``Team-Optimal Distributed MMSE Estimation in Tree and General Networks,'' Digital Signal Processing, Accepted, 2017.
        
  9. I. Utlu and S. S. Kozat, ``Resource-Aware Event Triggered Distributed Estimation Over Adaptive Networks,'' Digital Signal Processing, Accepted, 2017.
        
  10. D. Kari, N. D. Vanli, and S. S. Kozat, "Adaptive and Efficient Nonlinear Channel Equalization for Underwater Acoustic Communication," Physical Communications, Accepted, 2017.
        
  11. I. Delibalta, L. Baruh, and S. S. Kozat, "An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach," Journal of Electrical and Computer Engineering, Accepted, 2017.
        
  12. M. M. Neyshabouri and S. S. Kozat, ``Highly Efficient Nonlinear Regression for Big Data with Lexicographical Splitting,'' Signal, Image and Video Processing, vol. 11, iss. 3, pp. 391-398, 2017.
        
  13. B. C. Civek, I. Delibalta and S. S. Kozat, ``Highly Efficient Hierarchical Online Nonlinear Regression Using Second Order Methods,'' Digital Signal Processing, vol. 137, pp. 22-32, 2017.
        
  14. F. O. Kilic, M. O Sayin, I. Delibalta and S. S. Kozat, ``Computationally Highly Efficient Mixture of Adaptive Filters,'' Signal, Image and Video Processing, vol. 11(2), pp. 235-242, 2017.
        
  15. D. Kari, F. Khan, M. O. Sayin, and S. S. Kozat, "Robust Adaptive Algorithms for Underwater Acoustic Channel Estimation and Their Performance Analysis," Digital Signal Processing, vol. 68, pp. 57-68, 2017.
        
  16. N. D. Vanli, K. Gokcesu, M. O. Sayin, H. Yilmaz and S. S. Kozat, ``Sequential Prediction over Hierarchical Structures,'' IEEE Transactions on Signal Processing, vol. 64, iss. 23, pp. 6284-6298, 2016.
        
  17. F. Khan, I. A. Karatepe and S. S. Kozat, ``Universal Nonlinear Regression on High Dimensional Data Using Adaptive Hierarchical Trees,'' IEEE Transactions on Big Data, vol. 2, iss. 2, pp. 175-188, 2016.
        
  18. N. D. Vanli, H. Ozkan and S. S. Kozat, ``Online Classification via Self-Organizing Space Partitioning,'' IEEE Transactions on Signal Processing, vol. 64, iss. 15, pp. 3895-3908, 2016.
        
  19. N. D. Vanli, M. O. Sayin, I. Delibalta and S. S. Kozat, ``Sequential Nonlinear Learning for Distributed Multi-Agent Systems via Feedforward Networks,'' IEEE Transactions on Neural Networks and Learning Systems, iss. 99, pp. 1-13, 2016.
        
  20. H. Ozkan, F. Ozkan and S. S. Kozat, ``Online Anomaly Detection under Markov Statistics with Controllable Type-I Error,'' IEEE Transactions on Signal Processing, vol. 64, no.6, pp. 1435-1445, 2016.
        
  21. H. Ozkan, F. Ozkan, I. Delibalta and S. S. Kozat, "Efficient NP tests for Anomaly Detection over Birth-Death Type DTMCs", Journal of Signal Processing Systems, pp. 1-10, 2016.
        
  22. I. Delibalta K. Gokcesu, M. Simsek, L. Baruh and S. S. Kozat, ``Online Anomaly Detection With Nested Trees,'' IEEE Signal Processing Letters, vol. 23, iss. 12, pp. 1867-1871, 2016.
        
  23. N. D. Vanli, S. Tunc, M. A. Donmez and S. S. Kozat,  ``Growth Optimal Portfolios in Discrete-time Markets Under Proportional Transactions Costs," Digital Signal Processing, vol. 48, pp. 226-238, 2016.
      
  24. H. Ozkan, O. Pelvan and S. S. Kozat, ``Data Imputation through the Identification of Local Anomalies,'' IEEE Transactions on Neural Networks and Learning Systems, vol 26, pp. 2381-2395, 2015.
        
  25. H. Ozkan, M. A. Donmez, S. Tunc and S. S. Kozat, ``A Deterministic Analysis of an Online Convex Mixture of Experts Algorithm,'' IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 7, pp. 1575-1581, July 2015.
        
  26. N. D. Vanli and S. S. Kozat, ``A Unified Approach to Universal Prediction: Generalized Upper and Lower Bounds,'' IEEE Transactions on Neural Networks and Learning Systems, pp. 646-651, March 2015.
        
  27. M. O. Sayin, Y. Yilmaz, A. Demir and S. S. Kozat, ``The Krylov-proportionate Normalized Least Mean Fourth Approach: Formulation and Performance Analysis,'' Signal Processing, vol. 109, pp. 1-13, April 2015.
        
  28. N. D. Vanli, M. A. Donmez and S. S. Kozat, ``Robust Least Squares Methods Under Bounded Data Uncertainties,'' Digital Signal Processing, vol. 36, pp. 82-92, January 2015.
        
  29. N. D. Vanli and S. S. Kozat, ``A Comprehensive Approach to Universal Piecewise Nonlinear Regression Based on Trees,'' IEEE Transactions on Signal Processing, vol. 62, no. 20, pp. 5471-5486, Oct. 2014.
      
  30. M. O. Sayin and S. S. Kozat, ``Compressive Diffusion Strategies Over Distributed Networks for Reduced Communication Load,'' IEEE Transactions on Signal Processing, vol. 62, no. 20, pp. 5308-5323, Oct. 2014.
      
  31. M. O. Sayin, N. D. Vanli and S. S. Kozat, ``A Novel Family of Adaptive Filtering Algorithms Based on The Logarithmic Cost,'' IEEE Transactions on Signal Processing, vol. 62, no. 17, pp. 4411-4424, Sep. 2014.
      
  32. K. Kim, J. W. Choi, S. S. Kozat,  A. C. Singer, ``Low Complexity Turbo Equalization: A Clustering Approach," IEEE Communications Letters, vol. 18, no. 6, pp. 1063-1066, June 2014.
      
  33. H. Ozkan, A. Akman and S. S. Kozat, ``A Novel and Robust Parameter Training Approach for HMMs under Noisy and Partial Access to States,'' Signal Processing, vol. 94, pp. 490-497, January 2014.
           
  34. M. O. Sayin and S. S. Kozat, ``Single Bit and Reduced Dimension Diffusion Strategies Over Distributed Networks,'' IEEE Signal Processing Letters, vol. 20, no. 10, pp. 976-979, October 2013.
        
  35. S. Tunc, S. S. Kozat, ``Optimal Investment Under Transaction Costs: A Threshold Rebalanced Portfolio Approach,'' IEEE Transactions on Signal Processing, vol. 61, issue 12, pp. 3129-3142, June 2013.
         
  36. K. Kim, N. Kalantarova,   S. S. Kozat, A. C. Singer, ``Linear MMSE-Optimal Turbo Equalization Using Context Trees,'' IEEE Transactions on Signal Processing, vol. 61, issue 12, pp. 3041-3055, June 2013.
        
  37. M. A. Donmez, H. Inan, S. S. Kozat, ``Adaptive Mixture Methods Using Bregman Divergences,'' Digital Signal Processing, vol. 23, issue 1, pp. 88-97, January 2013.   
      
  38. M. A. Donmez, H. Inan and S. S. Kozat, ``Robust Estimation in Flat Fading Channels Under Bounded Channel Uncertainties,'' Digital Signal Processing, vol. 23, no. 5, pp. 1592-1601, September 2013.   
      
  39. S. S. Kozat, K. Guan, A. C. Singer, ``Tracking the best level set in a level-crossing analog-to-digital converter,'' Digital Signal Processing, vol. 23, issue 1, pp. 478-487, January 2013 .   
      
  40. M. A. Donmez, S. S. Kozat, ``Steady-state MSE Analysis of Convexly Constrained Mixture Methods,'' IEEE Transactions on Signal Processing, vol. 60, iss. 6, 3314-3321, 2012. 
           
  41. N. Kalantarova, S. S. Kozat, A. T. Erdogan, ``Robust Turbo Equalization Under Channel Uncertainties," IEEE Transactions on Signal Processing, vol. 60, iss. 1, 261-273, 2012. 
           
  42. S. S. Kozat, A. T. Erdogan, A. C. Singer, A. H. Sayed, ``A Transient Analysis of Affine Mixtures," IEEE Transactions on Signal Processing, vol. 59, iss. 1, 6227-6232, 2011.   
      
  43. S. S. Kozat, A. C. Singer, ``Universal semiconstant portfolios", Mathematical Finance, vol. 21, no. 2, pp. 293-311, April 2011.
        
  44. S. S. Kozat, A. C. Singer, A. J. Bean, "A Tree-Weighting Approach to Sequential Decision Problems with Multiplicative Loss," Signal Processing, vol. 92, issue 4, pp. 890-905, April 2011.
        
  45. Y. Yilmaz and S. S. Kozat, ``Competitive Randomized Nonlinear Prediction Under Additive Noise," IEEE Signal Processing Letters, vol. 17, issue 4, pp. 335-339, 2010.
      
  46. S. S. Kozat, A. T. Erdogan, A. C. Singer, A. H. Sayed, ``Steady-state MSE Performance Analysis of Mixture Approaches to Adaptive Filtering," IEEE Transactions on Signal Processing, vol.58, pp. 4050-4063, Aug. 2010. 
      
  47. S. S. Kozat, A. C. Singer, A. T. Erdogan, A. H. Sayed, ``Unbiased Model Combinations for Adaptive Filtering," IEEE Transactions on Signal Processing, vol. 58, pp. 4421-4427, Aug. 2010.
      
  48. S. S. Kozat, A. T.  Erdogan, ``Competitive linear estimation under model uncertainties," IEEE Transactions on Signal Processing, vol. 58, issue 4, pp. 2388-2393, April 2010.
      
  49. M. Vlachos, S. S. Kozat, P. Yu, ``Optimal Bounds for Fast Search on Compressed Time-Series Query Logs," ACM Journal of Web, vol. 2, issue 2, pp. 6.1-6.28.,  April 2010.
      
  50. S. S. Kozat, A. C. Singer, ``Universal Randomized Switching", IEEE Transactions on Signal Processing, vol. 58, issue 3, pp. 1922-1927, March 2010. 
      
  51. S. S. Kozat, A. C. Singer, ``Switching Strategies for Sequential Decision Problems with Multiplicative Loss with Application to Portfolios," IEEE Transactions on Signal Processing, vol. 57, issue 6, pp. 2192-2208, 2009.
      
  52. S. S. Kozat, A. C. Singer, ``Competitive Prediction Under Additive Noise", IEEE Transactions on Signal Processing, vol. 57, issue 9, pp. 3698-3703, 2009.
     
  53. A. C. Singer, J. Nelson, S. S. Kozat, ``Signal Processing for Underwater Acoustic Communications", IEEE Communications Magazine, Vol. 47, pp. 90-96, Jan. 2009. 
     
  54. S. S. Kozat, M. Vlachos, C. Lucchese, H. Van Herle, P. S. Yu, ``Embedding and Retrieving Private Metadata in Electrocardiograms", Journal of Medical Systems, Aug. 05, 2009.
     
  55. K. M. Guan, S. S. Kozat, A. C. Singer, ``Adaptive Reference Levels in a Level-Crossing Analog-to-Digital Converter," Eurasip Journal on Advances in Signal Processing, vol 2008, Issue 3, Jan. 2008.
     
  56. S. S. Kozat, A. Singer, ``Universal Switching  Linear Least Squares Prediction," IEEE Transactions on Signal Processing, vol. 56, issue 1, pp. 189-204, 2008.
     
  57. S. S. Kozat, A. C. Singer, G. Zeitler, ``Universal Piecewise Linear Prediction via Context Trees," IEEE Transactions on Signal Processing, pp. 3730-3745, July 2007.
     
  58. A. C. Singer, S. S. Kozat,  M. Feder, ``Universal linear least squares prediction: upper and lower bounds,"  IEEE Transactions on Information Theory, vol. 48, pp. 2354 -2362, Aug 2002.
      

Journal Papers (Preprints)

  1. O. F. Kilic, M. O. Sayin and S. S. Kozat, ``Team-Optimal Online Learning of Dynamic Parameters over Distributed Networks,'' IEEE Transactions on Network Science and Engineering, 2017.
        
  2. M. M. Neyshabouri, H. Ozkan and S. S. Kozat, ``A Highly Efficient Online Anomaly Detector Based on Infinite Depth Decision Trees,'' IEEE Transactions on Signal Processing, 2017.
        
  3. H. Ozkan and S. S. Kozat, ``Online Boosting with Multi-armed Bandits,'' IEEE Signal Processing Letters, 2017.
        
  4. T. Ergen and S. S. Kozat, ``Unsupervised and Semi-supervised Anomaly Detection with LSTM Neural Networks,'' IEEE Transactions on Signal Processing, 2017.
        
  5. E. Yar and S. S. Kozat, ``A Novel Short Text Categorization Model Based on Syllables and LSTM Networks,'' IEEE Transactions on Knowledge and Data Engineering, 2017.
        
  6. K. Gokcesu, M. M. Neyshabouri and S. S. Kozat, ``Multimodel Density Estimation with Growing and Decaying Trees,'' IEEE Signal Processing Letters, 2017.
        
  7. K. Gokcesu and S. S. Kozat, ``Minimax Optimal Algorithms for Expert Selection under Convex and Non-convex Loss Functions,'' IEEE Transactions on Signal Processing, 2017.
        
  8. M. M. Neyshabouri, K. Gokcesu and S. S. Kozat, ``An Asymptotically Optimal Contextual Bandit Algorithm Using Decision Trees,'' IEEE Transactions on Signal Processing, 2016.
        
  9. D. Kari, F. Khan and S. S. Kozat, ``A Novel Family of Boosted Online Regression Algorithms with Strong Theoretical Bounds,'' Knowledge and Information Systems, 2017.
        
  10. N. D. Vanli, M. O. Sayin and S. S. Kozat, ``Predicting Nearly As Well As the Optimal Twice Differentiable Regressor,'' Machine Learning, 2016.
        
  11. H. Ozkan and S. S. Kozat, ``Sequential and Randomized Quantization through AND-OR Graph Modeling,'' IEEE Transactions on Signal Processing, 2016.
        
  12. N. D. Vanli, S. Tunc and S. S. Kozat, ``Robust Portfolio Selection in Discrete-time Markets Under Transaction Costs,'' Digital Signal Processing, 2016.
        

Book Chapters

  1. S. S. Kozat, A. C. Singer, ``Parametric Estimation,'' Academic Press Library in Signal Processing, Sergios Theodoridis (Editor), Rama Chellappa (Editor), Elsevier, 2013 .

  2. N. D. Vanli, S. S. Kozat, ``Online Nonlinear Modeling via Self-Organizing Trees,'' to be published in Adaptive Learning Methods for Nonlinear System Modeling, Elsevier Publishing, Eds. D. Comminiello and J.C. Principe, 2018 .

Theses

  1. S. S. Kozat, ``Competitive Signal Processing,'' Ph.D. Dissertation, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL,  2004.
     
  2. S. S. Kozat, ``Multistage Adaptive Filters," MS. Thesis, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 2001.
     

Conference Papers

  1. T. Ergen and S. S. Kozat, ``Computationally Efficient Online Regression via LSTM Neural Networks,'' EUSIPCO,  2017.
     
  2. K. Gokcesu and S. S. Kozat, ``A General Framework for Adversarial Bandits'' EUSIPCO,  2017.
     
  3. K. Gokcesu and S. S. Kozat, ``A Rate Optimal Switching Bandit Algorithm'' EUSIPCO,  2017.
     
  4. B. C. Civek, S. Ciftci and S. S. Kozat, ``Computationally Feasible Online Second Order Time Series Prediction'' ICASSP,  2017.
     
  5. O. F. Kilic, M. O. Sayin, S. Ciftci and S. S. Kozat, ``An Efficient Mixture of Expert Method for Big Data Applications Computationally Feasible Online Second Order Time Series Prediction'' ICASSP,  2017.
     
  6. E. Yar, H. Ozkan, O. S. Pelvan, I. Delibalta, S. S. Kozat, ``Data Imputation via the Detection of Localized Corruptions,'' EUSIPCO,  2016.
     
  7. I. Utlu S. S. Kozat, ``Distributed Adaptive Filtering With Reduced Communication Load,'' EUSIPCO,  2016.
     
  8. Dariush Kari, Iman Marivani, Ibrahim Delibalta and S. S. Kozat, ``Boosted LMS-based Piecewise Linear Adaptive Filters'' EUSIPCO,  2016.
     
  9. O. Fatih Kilic, Ibrahim Delibalta and S. S. Kozat, ``Adaptive Hierarchical Space Partitioning for Online Classification'' EUSIPCO,  2016.
     
  10. O. Fatih Kilic, M. Omer Sayin, Ibrahim Delibalta and S. S. Kozat, ``An Efficient Mixture of Experts Method for Big Data Applicationss'' EUSIPCO,  2016.
     
  11. Mohammadreza Mohaghegh, Oguzhan Demir, Ibrahim Delibalta and S. S. Kozat, ``Nonlinear Regression with Lexicographical Splitting of Regressor Space'' EUSIPCO,  2016.
     
  12. E. Yar, I. Delibalta, L. Baruh, S. S. Kozat, "Online Text Classification and Regression for Real Life Tweet Analysis," IEEE Signal Processing and Communications Applications (SIU), 2016. 2016.
     
  13. M. Simsek, I. Delibalta, L. Baruh, S. S. Kozat, "A State Space Modeling of Causal Inference in Social Networks," IEEE Signal Processing and Communications Applications (SIU), 2016. 2016.
     
  14. O. F. Kilic, I. Delibalta S. S. Kozat, "Mixture of Set Membership Filters Approach for Big Data Signal Processing," IEEE Signal Processing and Communications Applications (SIU), 2016. 2016.
     
  15. O. Demir, M. Mohaghegh, I Delibalta, S. S. Kozat,"A Tree-Based Solution to Nonlinear Regression Problem," IEEE Signal Processing and Communications Applications (SIU), 2016. 2016.
     
  16. Burak C. Civek, Ibrahim Delibalta, Suleyman S. Kozat, "Boosted RLS and LMS Filters,"IEEE Signal Processing and Communications Applications (SIU), 2016. 2016.
     
  17. O. F. Kilic, N. D. Vanli, H. Ozkan, I. Delibalta, S. S. Kozat, "On-line Adaptive Space Partitioning Classifier," IEEE Signal Processing and Communications Applications (SIU), 2016. 2016.
     
  18. N. D. Vanli, M. O. Sayin, I. Delibalta and S. S. Kozat, ``Universal Online Prediction via Order Preserving Patterns," IEEE Workshop on Machine Learning for Signal Processing,   Boston, 2015.
     
  19. N. D. Vanli, M. O. Sayin, I. Delibalta and S. S. Kozat, ``Distributed Nonlinear Optimization Using Extreme Learning Machines," IEEE Workshop on Machine Learning for Signal Processing,   Boston, 2015.
     
  20. M. O. Sayin, N. D. Vanli, I. Delibalta and S. S. Kozat, ``Set Membership Filtering Approach for Mixture Combination of Adaptive Filters," IEEE Workshop on Machine Learning for Signal Processing,   Boston, 2015.
     
  21. F. Khan I. Delibalta and S. S. Kozat, ``High Dimensional Sequential Regression on Manifolds Using Adaptive Hierarchical Trees," IEEE Workshop on Machine Learning for Signal Processing,   Boston, 2015.
     
  22. M. O. Sayin, N. D. Vanli, I. Delibalta and S. S. Kozat, ``Efficient and Distributed Tracking of Evolving State," IEEE Workshop on Machine Learning for Signal Processing,   Boston, 2015.
     
  23. H. Ozkan, F. Ozkan, I. Delibalta and S. S. Kozat, ``Online Anomaly Detection with Constant False Alarm Rate" IEEE Workshop on Machine Learning for Signal Processing,   Boston, 2015.
     
  24. M. O. Sayin, N. D. Vanli and S. S. Kozat, ``Twice Universal Piecewise Linear Regression via Infinite Depth Context Tree," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Brisbane, Australia, 2015.
     
  25. M. O. Sayin, N. D. Vanli, I. Delibalta and S. S. Kozat, ``Optimal and Efficient Distributed Online Learning for Big Data," IEEE International Congress on Big Data, ,   NewYork, US, 2015.
     
  26. N. D. Vanli, M. O. Sayin, I. Delibalta and S. S. Kozat, ``A Scalable Approach for Online Hierarchical Big Data Mining," IEEE International Congress on Big Data, ,   NewYork, US, 2015.
     
  27. N. D. Vanli, M. O. Sayin, I. Delibalta and S. S. Kozat, ``Online Nonlinear Classification for High-Dimensional Data," IEEE International Congress on Big Data, ,   NewYork, US, 2015.
     
  28. M. O. Sayin, N. D. Vanli and S. S. Kozat, ``Logarithmic Regret Bound Over Diffusion Based Distributed Estimation," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Florence, Italy, 2014.
     
  29. M. O. Sayin, N. D. Vanli and S. S. Kozat, ``Improved Convergence Performance of Adaptive Algorithms Through Logarithmic Cost," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Florence, Italy, 2014.
     
  30. N. D. Vanli, M. A. Donmez and S. S. Kozat, ``Robust Regularized Least Squares Estimation in the Presence of Bounded Data Uncertainties," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Florence, Italy, 2014.
     
  31. M. O. Sayin and S. S. Kozat, ``Single Bit and Reduced Dimension Diffusion Strategies Over Adaptive Networks," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Florence, Italy, 2014.
     
  32. N. D. Vanli, M. O. Sayin, S. Ergut and S. S. Kozat ``Piecewise Nonlinear Regression via Decision Adaptive Trees," European Signal Processing Conference,  Lisbon, Portugal, 2014.
     
  33. N. D. Vanli, M. O. Sayin, S. Ergut and S. S. Kozat ``Comprehensive Lower Bounds on Sequential Prediction," European Signal Processing Conference,  Lisbon, Portugal, 2014.
     
  34. N. D. Vanli, M. O. Sayin, H. Yilmaz, T. Goze and S. S. Kozat ``Energy Consumption Forecasting via Order Preserving Pattern Matching," IEEE Global Conference on Signal and Information Processing, GlobalSIP,  Atlanta, Georgia, USA, 2014.
     
  35. M. O. Sayin, N. D. Vanli, T. Goze and S. S. Kozat ``Communication Efficient Channel Estimation Over Distributed Networks," IEEE Global Conference on Signal and Information Processing, GlobalSIP,  Atlanta, Georgia, USA, 2014.
     
  36. N. D. Vanli, M. O. Sayin and S. S. Kozat, ``Competitive Linear MMSE Estimation Under Structured Data Uncertainties," IEEE Signal Processing and Communications Applications Conference,   Trabzon, Turkey, 2014.
     
  37. M. O. Sayin and S. S. Kozat, ``Performance Analysis of Scalar Diffusion Strategy Over Distributed Network," IEEE Signal Processing and Communications Applications Conference   Trabzon, Turkey, 2014.
     
  38. M. O. Sayin, N. D. Vanli and S. S. Kozat, ``Robust Set-Membership Filtering Algorithms Against Impulsive Noise," IEEE Signal Processing and Communications Applications Conference   Trabzon, Turkey, 2014.
     
  39. N. D. Vanli and S. S. Kozat, ``Sequential Nonlinear Regression via Context Trees," IEEE Signal Processing and Communications Applications Conference   Trabzon, Turkey, 2014.
     
  40. H. Ozkan, M. A. Donmez, S. S. Kozat, ``Competitive and Online Piecewise Linear Classification," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Vancouver, 2013.
     
  41. S. Tunc, M. A. Donmez, S. S. Kozat, ``Growth Optimal Investment with Threshold Rebalancing Portfolios Under Transaction Costs," IEEE Int. Conf. Acou. Speech Sig., ICASSP,   Vancouver, 2013.
     
  42. M. A. Donmez and S. S. Kozat, ``Steady state MSE analysis of convexly constrained mixture methods ," Proceedings of Cognitive Information Processing Workshop,   pp. 1-4, 2012.
     
  43. M. A. Donmez and S. S. Kozat, ``Transient analysis of convexly constrained mixture methods," Machine Learning for Signal Processing (MLSP), 2012 IEEE International Workshop on,   pp. 1-5, 2012.
     
  44. H. Ozkan, A. Akman, S. Ergut, S. S. Kozat, ``A Novel Training Algorithm for PHMMs," Proceedings of Cognitive Information Processing Workshop,   2012.
     
  45. H. Ozkan, A. Akman and S. S. Kozat, ``Hidden Markov Model training with side information," Signal Processing and Communications Applications Conference (SIU), 2012 20th,  pp. 1-4, 2012.
     
  46. H. Ozkan, O. S. Pelvan, A. Akman and S. S. Kozat, ``A novel and incremental classification algorithm," Signal Processing and Communications Applications Conference (SIU), 2012 20th,  pp. 1-4, 2012.
     
  47. M. A. Donmez, S. Tunc, S. S. Kozat, ``Optimal Portfolios Under Transaction Costs in Discrete Time Markets," Proceedings of IEEE Workshop on Machine Learning for Signal Processing Workshop,   2012.
     
  48. M. A. Donmez, S. Tunc, S. S. Kozat, ``Growth Optimal Portfolios in Discrete Time Markets Under Transaction Costs," Proceedings of IEEE Conference on Signal Processing Advances in Wireless Communications,   2012.
     
  49. M. A. Donmez and S. S. Kozat, ``A Novel Adaptive Diversity Achieving Channel Estimation Scheme for LTE," Proceedings of International Conference on Mobile Computing and Networking,   2012.
     
  50. N. Kalantarova, M. A. Donmez and S. S. Kozat, ``Competitive Least Squares Problems with Bounded Data Uncertainties," IEEE Int. Conf. Acou. Speech Sig. Processing (ICASSP),   Kyoto, 2012.
     
  51. M. Inan, M. A. Donmez S. S. Kozat, ``Adaptive Mixture Methods Using Bregman Divergences," IEEE Int. Conf. Acou. Speech Sig. Processing (ICASSP),   Kyoto, 2012.
     
  52. N. Kalantarova, S. S. Kozat, A. T. Erdogan, ``Robust Turbo Equalization Under Channel Uncertainties," IEEE Radio and Wireless Symposium,   Phoenix, 2011.
     
  53. N. Kalantarova, S. S. Kozat, A. C. Singer, K. Kim, ``Nonlinear Turbo Equalization Using Context Trees," ITA Workshop, UCSD   2011.
     
  54. N. Kalantarova, S. S. Kozat, A. T. Erdogan, ``Robust Turbo Equalization Under Channel Uncertainties" Proceedings of IEEE Radio and Wireless Symposium, 2011.
     
  55. E. Bicici and S. S. Kozat, ``Adaptive Model Weighting and Transductive Regression for Predicting Best System Combinations" Proceedings of ACL Joint Fifth Statistical Machine Translation and Metrics, pp. 282-287, 07,  2010.
     
  56. A. C. Singer, K. Kim, J. W. Choi, S. S. Kozat, ``Nonlinear Adaptive filtering via Soft Clustured Linear Models" Proceedings of 44th Asilomar Conference on Signals, Systems and Computers, 11,  2010.
     
  57. Yasin Yilmaz and Suleyman S. Kozat,``A performance-weighted mixture of LMS filters," Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th , pp. 712-715, 2010.
     
  58. Andrew C. Singer and Suleyman S. Kozat, ``A competitive algorithm approach to adaptive filtering," Wireless Communication Systems (ISWCS), 2010 7th International Symposium on , pp. 350-354, 2010.
     
  59. M. Vlachos, S. S. Kozat, P. S. Yu, ``Optimal Distance Bounds on Compressed Time-series Query Logs," Proceedings of SIAM on Datamining, 2009.
     
  60. Yasin Yilmaz and Suleyman S. Kozat, ``An Extended Version of the NLMF Algorithm Based on Proportionate Krylov Subspace Projections," IEEE Conf. on Machine and Applications, , 2009.
     
  61. Suleyman S. Kozat, and Andrew C. Singer, ``A performance-weighted mixture of LMS filters," IEEE Int. Conf. on Acoustic Speech and Signal Processing, pp. 3101-3104, 2009.
     
  62. Alper T. Erdogan, Suleyman S. Kozat, Andrew C. Singer, ``Comparison of Convex Combination and Affine Combination of Adaptive Filters," IEEE Int. Conf. on Acoustic Speech and Signal Processing, 2009.
     
  63. Suleyman S. Kozat, Andrew C. Singer and Andrew Bean, ``Universal portfolios via context trees," IEEE Int. Conf. on Acoustic Speech and Signal Processing,  2008.
     
  64. Suleyman S. Kozat and Andrew C. Singer, ``Universal switching portfolios under transaction costs,'' IEEE Int. Conf. on Acoustic Speech and Signal Processing,  pp. 5404-5407, 2008.
     
  65. B. Mohanty, J. Hershey, P. Olsen, S. S. Kozat, V. Goel, ``Optimizing Speech Recognition Grammars Using a Measure of Similarity Between Hidden Markow Models," IEEE Int. Conf. on Acoustic Speech and Signal Processing, 2008.
     
  66. Suleyman S. Kozat, Andrew C. Singer, ``Universal Constant Rebalanced Portfolios with Switching," IEEE Int. Conf. on Acoustic Speech and Signal Processing,  pp. 1129-1132, April 2007.
     
  67. Georg Zeitler, Andrew C. Singer,  Suleyman S. Kozat, ``Universal Piecewise Linear Regression of Individual Sequences: Lower Bound,"  IEEE Int. Conf. on Acoustic Speech and Signal Processing,  Page(s) 841-844, April 2007.
     
  68. Suleyman S. Kozat, Karthik Visweswariah, Ramesh Gopinath, ``Efficient, Low Latency Adaptation for Speech Recognition," IEEE Int. Conf. on Acoustic Speech and Signal Processing,  Page(s) 777-780, April 2007.
     
  69. Suleyman S. Kozat, Andrew C. Singer, ``Universal Switching Linear Least squares Prediction ," IEEE Conference on Information Theory and Its Applications, 6-10, UCSD, La Jolla, CA, 2006.
     
  70. Andrew C. Singer and Suleyman S. Kozat, ``Universal Context Tree Least Squares Prediction ,"   IEEE International Symposium on Information Theory, 2006.
     
  71. Suleyman S. Kozat, Karthik Visweswariah, Ramesh Gopinath, ``Feature Adaptation Based on Gaussian Posteriors," IEEE Int. Conf. on Acoustic Speech and Signal Processing,  2006.
     
  72. Andrew C. Singer and Suleyman S. Kozat, ``Universal Context tree p-th Order Least Squares Prediction,"  IEEE Workshop on Machine Learning for Signal Processing, 2006.
     
  73. Suleyman S. Kozat, Andrew C. Singer, ``Universal Portfolios for Switching and Side-information," submitted to the IEEE Workshop on Machine Learning for Signal Processing, 2006.
     
  74. Suleyman S. Kozat, Andrew C. Singer, ``Minmax Optimal Prediction with Side Information",  IEEE Int. Conf. on Acoustic Speech and Signal Processing,  469-72, 2004.
     
  75. David Luengo, Suleyman S. Kozat, Andrew C. Singer, ``Universal Piecewise Linear Least squares Prediction," IEEE International Symposium on Information Theory, pp 198, 2004.
     
  76. Suleyman S. Kozat, M. Kivanc Mihcak, Ramarathnam Venkatesan, ``Robust Perceptual Image Hashing via Matrix Invariants," IEEE International Conference on Image Processing, pp 3443-46, 2004.
     
  77. Suleyman S. Kozat, Andrew C. Singer, ``A Lower Bound on the Performance of Sequential Prediction," IEEE International Symposium on Information Theory,  pp. 147-147, 2002.
     
  78. Suleyman S. Kozat, Andrew C. Singer, ``Further Results on Multistage Adaptation Algorithms," IEEE Int. Conf. on Acoustic Speech and Signal Processing,  pp. 1329-1332, Orlando, US, 2002.
     
  79. Suleyman S. Kozat, Andrew C. Singer, ``On Universal  Linear Prediction of Gaussian Data," IEEE Int. Conf. on Acoustic Speech and Signal Processing,  pp. 13-16, Istanbul, Turkey, 2000.
     
  80. Suleyman S. Kozat, Andrew C. Singer, ``Multi-Stage  Adaptive Signal Processing Algorithms," First IEEE Sensor Array and Multichannel Sig. Proc. Workshop, pp. 380-384, March, 2000 Massachusetts, USA.
     

Patents

  1. P. A. Chou, D. Florencio, S. S. Kozat, "Forward Error Correction for Media Transmissions", US 8553757.
     
  2. S. S. Kozat, R. Sarikaya, Y. Gao, ``Optimal Model Selection and Hypotheses Combination for Spoken Dialog Systems and Machine Translation," US 8275615.
     
  3. S. S. Kozat, R. Venkatesan, M. K. Mihcak, ``Digital Goods Representation Based on Matrix Invariants," US 20070076869.
     
  4. S. S. Kozat et al. "Optimal Model Selection and Hypotheses Combination for Recommendation Systems," filed 2016.
     
  5. S. S. Kozat et al. "A Sophisticated Intrusion Detection and Prevention System for Computer Networks", filed 2016.
     
  6. S. S. Kozat et al. "A Novel Method for Intrusion Detection Systems Based on State Information", filed 2016.
     
  7. S. S. Kozat et al. "Multi-Purpose Classification of Text Information Based On Syllables", filed 2016.
     
  8. S. S. Kozat et al. "A Method for Target Tracking over Distributed Sensor Nodes", filed 2016.
     
  9. S. S. Kozat et al. "A State Aware Recommendation System Based on User Profile Feature Vectors", filed 2016.