Publications

Journal Publications

1. Il Memming Park, Miriam L. R. Meister, Alexander C. Huk, Jonathan W. Pillow. Encoding and decoding in parietal cortex during sensorimotor decision-making. Nature Neuroscience 17, 1395–1403, 2014
2. Evan Archer*, Il Memming Park*, Jonathan Pillow. Bayesian Entropy Estimation for Countable Discrete Distributions. Journal of Machine Learning Research (JMLR) 15, 2833−2868, Oct 2014 arXiv:1302.0328 (* equal contribution)
3. Il Memming Park, Yuriy V. Bobkov, Barry W. Ache, José C. Príncipe. Intermittency coding in the primary olfactory system: A neural substrate for olfactory scene analysis. The Journal of Neuroscience 34(3): 941-952, January 15 2014 [pdf][news coverages]
4. Evan Archer, Il Memming Park, Jonathan W. Pillow. Bayesian and quasi-Bayesian estimators for mutual information from discrete data. Entropy 2013, 15, 1738-1755. (OA; special issue on Estimating Information-Theoretic Quantities from Data)
5. Il Memming Park, Sohan Seth, António R. C. Paiva, Lin Li, José C. Príncipe. Kernel methods on spike train space for neuroscience: a tutorial. IEEE Signal Processing Magazine, July 2013 [arXiv:1302.5964]
6. Lin Li, Il Memming Park, Austin Brockmeier, Sohan Seth, Badong Chen, Joseph Francis, Justin C. Sanchez, and José C. Príncipe. Adaptive Inverse Control of Neural Spatiotemporal Spike Patterns with a Reproducing Kernel Hilbert Space (RKHS) Framework. IEEE Transactions on Neural and Rehabilitation Systems Engineering, Volume 21, Issue 4, 532-543, July 2013
7. Yuriy Bobkov, Il Park, Kirill Ukhanov, José C. Príncipe, Barry W. Ache. Cellular basis for response diversity in the olfactory periphery. PLoS ONE 7(4): e34843 (2012) [blog post]
8. Il Memming Park, Sohan Seth, Murali Rao, José C. Príncipe. Strictly Positive Definite Spike Train Kernels for Point Process Divergences. Neural Computation Volume 24, Issue 8, August 2012 [pdf]
9. Lin Li, Il Memming Park, Sohan Seth, Justin C. Sanchez, José C. Príncipe. Functional Connectivity Dynamics Among Cortical Neurons: A Dependency Analysis, IEEE Transactions on Neural and Rehabilitation Systems Engineering, Volume 20, Issue 1 (2012) [movie]
10. Sohan Seth, Murali Rao, Il Park, José C. Príncipe. A Unified Framework for Quadratic Measures of Independence, IEEE Transactions on Signal Processing, Volume 59, Issue 8, Aug. 2011, 3624-3635. (code)
11. Weifeng Liu, Il Park, José C. Príncipe. An Information Theoretic Approach of Designing Sparse Kernel Adaptive Filters, IEEE Transactions on Neural Network, Volume 20, Issue 12, Dec. 2009, 1950-1961.
12. António R. C. Paiva, Il Park, José C. Príncipe. A Comparison of Binless Spike Train Measures, Neural Computing & Applications. Volume 19, Issue 3 (2010), page 405.
13. Weifeng Liu, Il Park, Yiwen Wang, José C. Príncipe. Extended Kernel Recursive Least Squares Algorithm, IEEE Transactions on Signal Processing, Volume 57, Issue 10, Oct. 2009, 3801-3814
14. Karl Dockendorf, Il Park, Ping He, José C. Príncipe, Thomas B. DeMarse. Liquid state machine and Dissociated Cortical Networks: The Separability, Biosystems, Volume 95, Issue 2, February 2009, 90-97
15. Jian-Wu Xu, António R. C. Paiva, Il Park, José C. Príncipe. A Reproducing Kernel Hilbert Space Framework for Information-Theoretic Learning, IEEE Transactions on Signal Processing, Vol. 56, No. 12. pp. 5891-5902. 2008
16. António R. C. Paiva, Il Park, José C. Príncipe. A Reproducing Kernel Hilbert Space framework for Spike Trains, Neural Computation, Volume 21, Number 2, February 2009, 424-449
17. Il Park, António R. C. Paiva, José C. Príncipe, Thomas B. DeMarse. An Efficient Algorithm for Continuous-time Cross Correlogram of Spike Trains, Journal of Neuroscience Methods, Volume 168, Issue 2, 15 March 2008, 514-523

Conference Publications (peer-reviewed papers)

1. Yuan Zhao, Il Memming Park. Interpretable Nonlinear Dynamic Modeling of Neural Trajectories. Neural Information Processing Systems (NIPS) 2016 [arXiv]
2. Anqi Wu, Il Memming Park, Jonathan Pillow. Convolutional spike-triggered covariance analysis for neural subunit models. Neural Information Processing Systems (NIPS) 2015 [pdf]
3. Il Memming Park, Sohan Seth, Steven Van Vaerenbergh. Probabilistic Kernel Least Mean Squares Algorithms. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2014 [poster]
4. Il Memming Park, Evan Archer, Kenneth Latimer, Jonathan Pillow. Universal models for binary spike patterns using centered Dirichlet processes. Neural Information Processing Systems (NIPS) 2013 (25.4% acceptance rate) [pdf+supplement][code][poster]
5. Il Memming Park*, Evan Archer*, Nicholas Priebe, Jonathan Pillow. Spectral methods for neural characterization using generalized quadratic models. Neural Information Processing Systems (NIPS) 2013 (25.4% acceptance rate, * equal contribution) [pdf]
6. Evan Archer, Il Memming Park, Jonathan Pillow. Bayesian entropy estimation for binary spike train data using parametric prior knowledge. Neural Information Processing Systems (NIPS) 2013 (spotlight, top 5% of submitted) [pdf][code][spotlight video]
7. Evan Archer*, Il Memming Park*, Jonathan W. Pillow. Bayesian estimation of discrete entropy with mixtures of stick breaking priors. Neural Information Processing Systems (NIPS) 2012 (25.2% acceptance rate, * equal contribution) [corrected preprint]
8. Il Memming Park, Jonathan W. Pillow. Bayesian Spike Triggered Covariance Analysis. Neural Information Processing Systems (NIPS) 2011 (21.8% acceptance rate) [blog post][pdf][supplement]
9. Lin Li, Il Memming Park, Sohan Seth, John Choi, Joseph T. Francis, Justin C. Sanchez, José C. Príncipe. An adaptive decoder from spike trains to micro-stimulationusing kernel least-mean-square (KLMS) algorithm. IEEE Machine learning for Signal Processing (MLSP) 2011
10. Il Park, Sohan Seth, Murali Rao, José C. Príncipe. Estimation of symmetric chi-square divergence for point processes. IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) 2011 (presentation) [pdf]
11. Sohan Seth, Il Park, Austin J. Brockmeier, Mulugeta Semework, John Choi, Joe Francis, José C. Príncipe. A Novel Family of Non-Parametric Cumulative based Divergences for Point Processes. Neural Information Processing Systems (NIPS) 2010 [blog post][pdf]
12. Austin J. Brockmeier, Il Park, Babak Mahmoudi, Justin C. Sanchez, José C. Príncipe. Spatio-Temporal Clustering of Firing Rates for Neural State Estimation, IEEE International EMBS Conference, 2010
13. Lin Li, Sohan Seth, Il Park, Justin C. Sanchez, José C. Príncipe. Neuronal Functional Connectivity Dynamics in Cortex: An MSC-based Analysis, IEEE International EMBS Conference, 2010
14. Il Park, José C. Príncipe. Quantification of Inter-trial Non-stationarity in Spike Trains from Periodically Stimulated Neural Cultures, IEEE International Conference on Acoustics, Speech and Signal Processing 2010, Special session on “Multivariate Analysis of Brain Signals: Methods and Applications” (accepted #3459, 48.8% acceptance rate) [blog post]
15. Lin Li, Sohan Seth, Il Park, Justin C. Sanchez, José C. Príncipe. Estimation and Visualization of Neuronal Functional Connectivity in Motor Tasks, IEEE International EMBS Conference 2009 Paper #1672
16. Sohan Seth, Il Park, José C. Príncipe. A New Nonparametric Measure of Conditional Independence, IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) 2009 Paper #3858
17. António R. C. Paiva, Il Park, Justin Sanchez, José C. Príncipe. Peri-event Cross-Correlation over Time for Analysis of Interactions in Neuronal Firing, International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2008
18. Il Park, José C. Príncipe. Correntropy based Granger causality, IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) 2008
19. António R. C. Paiva, Il Park, José C. Príncipe. Reproducing Kernel Hilbert Spaces for Spike Train Analysis, IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) 2008
20. António R. C. Paiva, Sudhir Rao, Il Park, José C. Príncipe. Spectral Clustering of Synchronous Spike Trains, IEEE International Joint Conference on Neural Networks (IJCNN), 2007
21. António R. C. Paiva, Il Park, José C. Príncipe. Innovating Signal Processing for Spike Train Data, International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Lyon, France, 2007
22. Il Park, António R. C. Paiva, José C. Príncipe, John G. Harris. A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters, IEEE International Joint Conference on Neural Networks (IJCNN), 2007
23. Il Park, Dongming Xu, Thomas B. DeMarse, José C. Príncipe. Modeling of Synchronized Burst in Dissociated Cortical Tissue: An Exploration of Parameter Space, IEEE International Joint Conference on Neural Networks (IJCNN), 2006
24. Il Park and Jong C. Park. Modeling Causality in Biological Pathways for Logical Identification of Drug Targets, Bioinfo, Busan, Korea, September, 2005.

Conference Abstracts

1. Jacob Yates, Evan Archer, Alexander C. Huk, Il Memming Park. Canonical correlations reveal co-variability between spike trains and local field potentials in area MT. CNS 2015 (Prague) [poster]
2. Il Memming Park, Jacob Yates, Alex Huk, Jonathan Pillow. Dynamic correlations between visual and decision areas during perceptual decision-making. COSYNE 2015
3. Anqi Wu, Il Memming Park, Jonathan Pillow. Convolutional spike-triggered covariance analysis for estimating subunit models. COSYNE 2015
4. Il Memming Park, Evan Archer, Kenneth Latimer, Jonathan Pillow. Scalable nonparametric models for binary spike patterns. COSYNE 2014
5. Alexander Huk, Jacob Yates, Leor Katz, Il Memming Park, Jonathan Pillow. Dissociated functional significance of choice-related activity across the primate dorsal stream. COSYNE 2014 (talk by Alex Huk)
6. Il Memming Park, Evan Archer, Jonathan Pillow. Bayesian entropy estimators for spike trains. CNS 2013 [BMC Neuroscience 2013, 14(Suppl 1):P316]
7. Il Memming Park, Evan Archer, Nicholas Priebe, Jonathan Pillow. Got a moment or two? Neural models and linear dimensionality reduction. COSYNE 2013
8. Jonathan Pillow, Il Memming Park. Beyond Barlow: a Bayesian theory of efficient neural coding. COSYNE 2013
9. Jacob Yates, Il Memming Park, Lawrence Cormack, Jonathan Pillow, Alexander Huk. Precise characterization of multiple LIP neurons in relation to stimulus and behavior. COSYNE 2013
10. Evan Archer, Il Memming Park, Jonathan Pillow. Semi-parametric Bayesian entropy estimation for binary spike trains. COSYNE 2013
11. Il Memming Park, Miriam L. R. Meister, Alexander C. Huk, Jonathan W. Pillow. Deciphering the code for sensorimotor decision-making at the level of single neurons in parietal cortex. SfN 2012 (Oral presentation)
12. Il Memming Park, Jonathan Pillow. Bayesian spike-triggered covariance and the elliptical LNP model. COSYNE 2012 [blog post]
13. Evan Archer, Il Memming Park, Jonathan Pillow. Bayesian entropy estimation for infinite neural alphabets. COSYNE 2012 [blog post]
14. Il Memming Park, Sohan Seth, José C. Príncipe. Spike Train Kernel Methods for Neuroscience. JSM 2011 (invited speaker)
15. Il Memming Park, Jonathan Pillow, Miriam Meister, Alexander Huk. Detailed encoding and decoding of choice-related information from LIP spike trains. COSYNE 2011 [pdf]
16. Yuriy Bobkov, Kirill Ukhanov, Il Park, José C. Príncipe, Barry W. Ache. Measuring Ensemble Activity in Lobster ORNs through Calcium Imaging (AchemS 2010)
17. António R. C. Paiva, Il Park. Which measure should we use for unsupervised spike train learning? (Statistical Analysis of Neuronal Data (SAND5)) 2010
18. Il Park, José C. Príncipe. Significance test for spike trains based on finite point process estimation. (Society for Neuroscience 2009) [blog post] poster# 789.1/GG119
19. Yuriy Bobkov, Il Park, Kirill Ukhanov, José C. Príncipe, Barry W. Ache. Population coding within an ensemble of rhythmically active primary olfactory receptor neurons. (Society for Neuroscience 2009) poster# 349.9/V18
20. Il Park, Yuriy Bobkov, Kirill Ukhanov, Barry W. Ache, José C. Príncipe. Input Driven Synchrony of Oscillating Olfactory Receptor Neurons: A Computational Modeling Study, (AChemS 2009) [blog post]
21. Il Park, Murali Rao, Thomas B. DeMarse, José C. Príncipe. Point Process Model for Precisely Timed Spike Trains (COSYNE 2009) [blog post]
22. António R. C. Paiva, Il Park, José C. Príncipe, Reproducing Kernel Hilbert Spaces for Spike Train Analysis, Conference on Computational Neuroscience, 2008 (presented by José C. Príncipe)
23. Il Park, António R. C. Paiva, José C. Príncipe, Thomas B. DeMarse. An Efficient Computation of Continuous-time Correlogram of Spike Trains, COSYNE 2007, Salt Lake City, Utah, February 22-25, 2007 [png]

ArXiv only (some are under review)

1. Yuan Zhao, Il Memming Park. Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains. arXiv:1604.03053 (2016)
2. Evan Archer, Il Memming Park, Lars Büsing, John Cunningham, Liam Paninski. Black box variational inference for state space models. arXiv:1511.07367 (2015)
3. Il Memming Park, Sohan Seth, Steven Van Vaerenbergh. Bayesian Extensions of Kernel Least Mean Squares. arXiv:1310.5347 (2013)
4. Il Memming Park, Marcel Nassar, Mijung Park. Active Bayesian Optimization: Minimizing Minimizer Entropy. arXiv:1202.2143v1 (2012) [blog post]

Book Chapters

1. António R. C. Paiva, Il Park, José C. Príncipe, Justin C. Sanchez. Instantaneous cross-correlation analysis of neural ensembles with high temporal resolution. (in Introduction to Neural Engineering for Motor Rehabilitation, edited by D. Farina, W. Jensen, M. Akay. John Wiley & Sons, 2013)
2. António R. C. Paiva, Il Park, José C. Príncipe. Inner products for representation and learning in the spike train domain. (Book chapter in “Stastical Signal Processing for Neuroscience“, Academic press, edited by Karim G. Oweiss) [amazon] [science direct]
3. José C. Príncipe, Jianwu Xu, Robert Jenssen, Antonio Paiva, Il Park. A Reproducing Kernel Hilbert Space Framework for Information-Theoretic Learning. (in “Information Theoretic Learning: Renyi’s Entropy and Kernel Perspectives” edited by José C. Príncipe from Springer, 2010)
4. António R. C. Paiva, Il Park, José C. Príncipe. Optimization in Reproducing Kernel Hilbert Spaces of Spike Trains, (Book chapter in “optimization in Neuroscience”, Springer Optimization and Its Applications series, edited by Panos Pardalos)

Thesis and Dissertation

1. Il Park. Capturing spike train similarity structure: A point process divergence approach. Ph.D. dissertation (2010)
2. Il Park. Continuous time correlation analysis techniques for spike trains. M.S. thesis (2007)

Talks

1. I. Memming Park. Scaling up with Bayes. COSYNE workshop 2014
2. Il Memming Park. Deciphering the code for sensorimotor decision-making at the level of single neurons in parietal cortex. Invited seminar, KIST and POSTECH 2012 Dec.
3. Il Memming Park, A Neural Substrate for Olfactory Scene Analysis in Lobster, CNS workshop 2012
4. Il Park, Neural coding by Input driven synchrony of Spontaneously bursting Olfactory receptor neurons, CNEL seminar, 2009
5. Il Park, Noise or Signal in Spike Trains from Neuronal Culture, CNEL seminar, 2008
6. Il Park, Thomas B. DeMarse, José C. Príncipe. Liquid State Machines and Cultured Cortical Networks: What we have learned, Collaborative Research in Computational Neuroscience (CRCNS) PI meeting 2008
7. Il Park, Karl Dockendorf, Thomas B. DeMarse, José C. Príncipe. Cultured Liquid State Machine, Collaborative Research in Computational Neuroscience (CRCNS) PI meeting 2007 (poster presentation)
8. Il Park, Synchrony of Neuronal Culture and RKHS on Spike Trains, CNEL seminar, 2006
9. José C. Príncipe, Thomas B. DeMarse. Design, Analysis and Validation of Biologically Plausible Computational Models, Collaborative Research in Computational Neuroscience (CRCNS) PI meeting 2006 (partially presented by Il Park and Karl Dockendorf)

my Google scholar page

CHAPTER 9

A REPRODUCING KERNEL HILBERT SPACE FRAMEWORK FOR

INFORMATION-THEORETIC LEARNING

Chapter Co-authors: Jianwu Xu, Robert Jenssen, Antonio Paiva, Il Park