Bohren, Jonathan, Tully Foote, Jim Keller, Alex Kushleyev, Daniel Lee, Alex Stewart, Paul Vernaza, Jason Derenick, John Spletzer, and Brian Satterfield. “Little Ben: The Ben Franklin Racing Team’s Entry in the 2007 DARPA Urban Challenge.” Journal of Field Robotics 25, no. 9 (September 1, 2008): 598–614. doi:10.1002/rob.20260.

Brener, I., D. D. Lee, P. P. Mitra, D. L. Philen, and D. J. Thomson. “A New Technique for Zero-Dispersion Wavelength Mapping in Single Mode Fiber with High Spatial Resolution.” In European Conf. Opt. Comm. Proc., 1998.

Brener, I., P. P. Mitra, D. D. Lee, D. J. Thomson, and D. L. Philen. “High-Resolution Zero-Dispersion Wavelength Mapping in Single-Mode Fiber.” Optics Letters 23, no. 19 (October 1, 1998): 1520–22. doi:10.1364/OL.23.001520.

Butzke, J., K. Daniilidis, A. Kushleyev, D. D. Lee, M. Likhachev, C. Phillips, and M. Phillips. “The University of Pennsylvania MAGIC 2010 Multi-Robot Unmanned Vehicle System.” Journal of Field Robotics 29, no. 5 (September 1, 2012): 745–61. doi:10.1002/rob.21437.

Chen, S. H., D. D. Lee, K. Kimishima, H. Jinnai, and T. Hashimoto. “Measurement of the Gaussian Curvature of the Surfactant Film in an Isometric Bicontinuous One-Phase Microemulsion.” Phys. Rev. E 54 (1996): 6526–31.

Chen, Sow-Hsin, Daniel Lee, and Szu-Li Chang. “Visualization of 3D Microstructure of Bicontinuous Microemulsions by Combined SANS Experiments and Simulations.” Journal of Molecular Structure 296, no. 3 (August 1993): 259–64. doi:10.1016/0022-2860(93)80141-H.

Chitta, Sachin, Paul Vemaza, Roman Geykhman, and Daniel D. Lee. “Proprioceptive Localilzatilon for a Quadrupedal Robot on Known Terrain,” 4582–87. IEEE, 2007. doi:10.1109/ROBOT.2007.364185.

Chung, SueYeon. “Linear Readout of Object Manifolds.” Physical Review E 93, no. 6 (2016). doi:10.1103/PhysRevE.93.060301.

Clingerman, C., and D.D. Lee. “Estimating Manipulability of Unknown Obstacles for Navigation in Indoor Environments.” In 2014 IEEE International Conference on Robotics and Automation (ICRA), 2771–78, 2014. doi:10.1109/ICRA.2014.6907256.

Crammer, K., and D.D. Lee. “Room Impulse Response Estimation Using Sparse Online Prediction and Absolute Loss,” 3:III – 748 – III – 751. IEEE, 2006. doi:10.1109/ICASSP.2006.1660762.

Crammer, Koby, and Daniel D. Lee. “Learning via Gaussian Herding.” In Advances in Neural Information Processing Systems 23, edited by J. D. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, and A. Culotta, 451–59. Curran Associates, Inc., 2010. http://papers.nips.cc/paper/3893-learning-via-gaussian-herding.pdf.

———. “Online Discriminative Learning of Phoneme Recognition via Collections of Generalized Linear Models.” In 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012, Kyoto, Japan, March 25-30, 2012, 1961–64. IEEE, 2012. doi:10.1109/ICASSP.2012.6288290.

Der, Ricky, and Daniel Lee. “Large-Margin Classification in Banach Spaces.” In Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, AISTATS 2007, San Juan, Puerto Rico, March 21-24, 2007, edited by Marina Meila and Xiaotong Shen, 2:91–98. JMLR Proceedings. JMLR.org, 2007. http://www.jmlr.org/proceedings/papers/v2/der07a.html.

Der, Ricky, and Daniel D. Lee. “Beyond Gaussian Processes: On the Distributions of Infinite Networks.” In Advances in Neural Information Processing Systems 18, edited by Y. Weiss, B. Schölkopf, and J. C. Platt, 275–82. MIT Press, 2006. http://papers.nips.cc/paper/2869-beyond-gaussian-processes-on-the-distributions-of-infinite-networks.pdf.

Downs, Oliver B., David J. C. MacKay, and Daniel D. Lee. “The Nonnegative Boltzmann Machine.” In Advances in Neural Information Processing Systems 12, edited by S. A. Solla, T. K. Leen, and K. Müller, 428–34. MIT Press, 2000. http://papers.nips.cc/paper/1743-the-nonnegative-boltzmann-machine.pdf.

Feng, Y.P., S.K. Sinha, C.A. Melendres, and D.D. Lee. “X-Ray off-Specular Reflectivity Studies of Electrochemical Pitting of Cu Surfaces in Sodium Bicarbonate Solution.” Physica B: Condensed Matter 221, no. 1–4 (April 1996): 251–56. doi:10.1016/0921-4526(95)00934-5.

Ham, J. H., D. D. Lee, and L. K. Saul. “Learning High Dimensional Correspondences with Low Dimensional Manifolds.” In International Conference on Machine Learning, Vol. Workshop on the continuum from labeled to unlabeled data, 2003.

Ham, Jihun, Daniel D. Lee, Sebastian Mika, and Bernhard Schölkopf. “A Kernel View of the Dimensionality Reduction of Manifolds.” In Proceedings of the Twenty-First International Conference on Machine Learning, 47 – . ICML ’04. New York, NY, USA: ACM, 2004. doi:10.1145/1015330.1015417.

Hamm, Jihun, and Daniel D. Lee. “Extended Grassmann Kernels for Subspace-Based Learning.” In Advances in Neural Information Processing Systems 21, edited by D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, 601–8. Curran Associates, Inc., 2009. http://papers.nips.cc/paper/3433-extended-grassmann-kernels-for-subspace-based-learning.pdf.

———. “Grassmann Discriminant Analysis: A Unifying View on Subspace-Based Learning.” In Proceedings of the 25th International Conference on Machine Learning, 376–83. ICML ’08. New York, NY, USA: ACM, 2008. doi:10.1145/1390156.1390204.

Huh, Jinwook, and D. D. Lee. “Learning High-Dimensional Mixture Models for Fast Collision Detection in Rapidly-Exploring Random Trees.” In 2016 IEEE International Conference on Robotics and Automation (ICRA), 63–69, 2016. doi:10.1109/ICRA.2016.7487116.

J. Ham, L. K. Saul, D. D. Lee. “Semisupervised Alignment of Manifolds.” In International Workshop on Artificial Intelligence and Statistics, 2004.

Jihun Ham, Ikkjin Ahn, and D. Lee. “Learning a Manifold-Constrained Map between Image Sets: Applications to Matching and Pose Estimation,” 1:817–24. IEEE, 2006. doi:10.1109/CVPR.2006.165.

Jihun Ham, Yuanqing Lin, and D.D. Lee. “Learning Nonlinear Appearance Manifolds for Robot Localization,” 2971–76. IEEE, 2005. doi:10.1109/IROS.2005.1545149.

Jinnai, H., T. Hashimoto, D. D. Lee, and S. H. Chen. “Morphological Characterization of Bicontinuous Phase-Separated Polymer Blends and One-Phase Microemulsions.” Macromolecules 30 (1997): 130–36.

Lee, B., and D. D. Lee. “Learning Anisotropic ICP (LA-ICP) for Robust and Efficient 3D Registration.” In 2016 IEEE International Conference on Robotics and Automation (ICRA), 5040–45, 2016. doi:10.1109/ICRA.2016.7487709.

Lee, D. D., J. Barker, and S. H. Chen. “Absolute Calibration of Small Angle Neutron Scattering Data Using Strong Coherent Scattering.” J. Phys. (Paris) IV C8 (1993): 431–34.

Lee, D. D., and S. H. Chen. “Geometry of Bicontinuous Microemulsions as Revealed by SANS and Simulations.” Il Nuovo Cimento 16D (1994): 1357–66.

———. “Local Geometry of Surfactant Monolayers in a Ternary Microemulsion System.” Phys. Rev. Lett. 73 (1994): 106–9.

Lee, D. D., S. H. Chen, C. F. Majkrzak, and S. K. Satija. “Bulk and Surface Correlations in a Microemulsion.” Phys. Rev. E 52 (1995): R29–33.

Lee, D. D., J. H. Choy, and J. K. Lee. “Computer Generation of Binary and Ternary Phase Diagrams via a Convex Hull Method.” Journal of Phase Equilibria 13, no. 4 (August 1, 1992): 365–72. doi:10.1007/BF02674981.

Lee, D. D., B. Y. Reis, H. S. Seung, and D. W. Tank. “Nonlinear Network Models of the Oculomotor Integrator.” In Computational Neuroscience, 5:371, 1997.

Lee, D. D., and H. S. Seung. “Biologically Inspired Computation and Learning in Sensorimotor Systems.” In Proc. SPIE: Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation IV, edited by Bruno Bosacchi, David B. Fogel, and James C. Bezdek, 4479:4–11, 2001.

———. “Learning in Intelligent Embedded Systems.” In Usenix Workshop on Embedded Systems, 1999.

Lee, D.D., B.R. McClain, B.L. Carvalho, S.G.J. Mochrie, J.D. Litster, S.H. Chen, C.F. Majkrzak, and S.K. Satija. “Interfacial Scattering from Surfactant Monolayers in Microemulsions.” Physica B: Condensed Matter 221, no. 1–4 (April 1996): 296–300. doi:10.1016/0921-4526(95)00940-X.

Lee, Daniel D, Pedro A Ortega, and Alan A Stocker. “Dynamic Belief State Representations.” Current Opinion in Neurobiology 25 (April 2014): 221–27. doi:10.1016/j.conb.2014.01.018.

Lee, Daniel D, and H. S. Seung. “A Neural Network Based Head Tracking System.” In Advances in Neural Information Processing Systems 10, edited by M. I. Jordan, M. J. Kearns, and S. A. Solla, 908–14. MIT Press, 1998. http://papers.nips.cc/paper/5221-a-neural-network-based-head-tracking-system.pdf.

Lee, Daniel D., Uri Rokni, and Haim Sompolinsky. “Algorithms for Independent Components Analysis and Higher Order Statistics.” In Advances in Neural Information Processing Systems 12, edited by S. A. Solla, T. K. Leen, and K. Müller, 491–97. MIT Press, 2000. http://papers.nips.cc/paper/1639-algorithms-for-independent-components-analysis-and-higher-order-statistics.pdf.

Lee, Daniel D., and H. Sebastian Seung. “Algorithms for Non-Negative Matrix Factorization.” In Advances in Neural Information Processing Systems 13, edited by T. K. Leen, T. G. Dietterich, and V. Tresp, 556–62. MIT Press, 2001. http://papers.nips.cc/paper/1861-algorithms-for-non-negative-matrix-factorization.pdf.

———. “Learning the Parts of Objects by Non-Negative Matrix Factorization.” Nature 401, no. 6755 (October 21, 1999): 788–91. doi:10.1038/44565.

———. “Unsupervised Learning by Convex and Conic Coding.” In Advances in Neural Information Processing Systems 9, edited by M. C. Mozer, M. I. Jordan, and T. Petsche, 515–21. MIT Press, 1997. http://papers.nips.cc/paper/1242-unsupervised-learning-by-convex-and-conic-coding.pdf.

Lee, Daniel D., and Haim Sompolinsky. “Learning a Continuous Hidden Variable Model for Binary Data.” In Advances in Neural Information Processing Systems 11, edited by M. J. Kearns, S. A. Solla, and D. A. Cohn, 515–21. MIT Press, 1999. http://papers.nips.cc/paper/1580-learning-a-continuous-hidden-variable-model-for-binary-data.pdf.

Lee, Daniel D., Seung-Joon Yi, Stephen G. McGill, Yida Zhang, Larry Vadakedathu, Samarth Brahmbhatt, Richa Agrawal, and Vibhavari Dasagi. “RoboCup 2013 Humanoid Kidsize League Winner.” In RoboCup 2013: Robot World Cup XVII [papers from the 17th Annual RoboCup International Symposium, Eindhoven, The Netherlands, July 1, 2013], edited by Sven Behnke, Manuela M. Veloso, Arnoud Visser, and Rong Xiong, 8371:49–55. Lecture Notes in Computer Science. Springer, 2013. doi:10.1007/978-3-662-44468-9_5.

Lee, Dean, Nathan Salwen, and Daniel Lee. “The Diagonalization of Quantum Field Hamiltonians.” Physics Letters B 503, no. 1–2 (March 22, 2001): 223–35. doi:10.1016/S0370-2693(01)00197-6.

Lin, Y., P. Vernaza, J. Ham, and D.D. Lee. “Cooperative Relative Robot Localization with Audible Acoustic Sensing,” 3764–69. IEEE, 2005. doi:10.1109/IROS.2005.1545056.

Lin, Yuanqing, Jingdong Chen, Youngmoo Kim, and Daniel D. Lee. “Blind Channel Identification for Speech Dereverberation Using l1-Norm Sparse Learning.” In Advances in Neural Information Processing Systems 20, edited by J. C. Platt, D. Koller, Y. Singer, and S. T. Roweis, 921–28. Curran Associates, Inc., 2008. http://papers.nips.cc/paper/3262-blind-channel-identification-for-speech-dereverberation-using-l1-norm-sparse-learning.pdf.

———. “Blind Sparse-Nonnegative (BSN) Channel Identification for Acoustic Time-Difference-of-Arrival Estimation,” 106–9. IEEE, 2007. doi:10.1109/ASPAA.2007.4392996.

Lin, Yuanqing, and Daniel D. Lee. “Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation.” In Advances in Neural Information Processing Systems 17, edited by L. K. Saul, Y. Weiss, and L. Bottou, 809–16. MIT Press, 2005. http://papers.nips.cc/paper/2710-bayesian-regularization-and-nonnegative-deconvolution-for-time-delay-estimation.pdf.

McClain, B. R., D. D. Lee, B. L. Carvalho, S. G. J. Mochrie, S. H. Chen, and J. D. Litster. “X-Ray Reflectivity Study of an Oil-Water Interface in Equilibrium with a Middle-Phase Microemulsion.” Phys. Rev. Lett. 72 (1994): 246–49.

McGill, Stephen G., and Daniel D. Lee. “Cooperative Humanoid Stretcher Manipulation and Locomotion,” 429–33. IEEE, 2011. doi:10.1109/Humanoids.2011.6100906.

McGill, Stephen G., Seung-Joon Yi, Yida Zhang, and Daniel D. Lee. “Extensions of a RoboCup Soccer Software Framework.” In RoboCup 2013: Robot World Cup XVII [papers from the 17th Annual RoboCup International Symposium, Eindhoven, The Netherlands, July 1, 2013], edited by Sven Behnke, Manuela M. Veloso, Arnoud Visser, and Rong Xiong, 8371:608–15. Lecture Notes in Computer Science. Springer, 2013. doi:10.1007/978-3-662-44468-9_56.

Melendres, C. A., Y. P. Feng, D. D. Lee, and S. K. Sinha. “X‐Ray Diffuse Scattering for the In Situ Study of Electrochemically Induced Pitting on Metal Surfaces.” Journal of The Electrochemical Society 142, no. 1 (1, 1995): L19–21. doi:10.1149/1.2043974.

Mensh, B. D., E. Aksay, D. D. Lee, H. S. Seung, and D. W. Tank. “Spontaneous Eye Movements in Goldfish: Oculomotor Integrator Performance, Plasticity, and Dependence on Visual Feedback.” Vision Research 44, no. 7 (March 2004): 711–26.

Nagatani, Keiji, Alex Kushleyev, and Daniel D. Lee. “Sensor Information Processing in Robot Competitions and Real World Robotic Challenges.” Advanced Robotics 26, no. 14 (September 2012): 1539–54. doi:10.1080/01691864.2012.694624.

Noh, Yung-kyun, Frank Park, and Daniel D. Lee. “Diffusion Decision Making for Adaptive K-Nearest Neighbor Classification.” In Advances in Neural Information Processing Systems 25, edited by F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger, 1925–33. Curran Associates, Inc., 2012. http://papers.nips.cc/paper/4734-diffusion-decision-making-for-adaptive-k-nearest-neighbor-classification.pdf.

Noh, Yung-Kyun, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, and Daniel D. Lee. “Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence.” In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, 33:669–77. JMLR Proceedings. JMLR.org, 2014. http://jmlr.org/proceedings/papers/v33/noh14.html.

Noh, Yung-Kyun, Byoung-Tak Zhang, and Daniel D. Lee. “Fluid Dynamics Models for Low Rank Discriminant Analysis.” In International Conference on Artificial Intelligence and Statistics, 565–72, 2010. http://machinelearning.wustl.edu/mlpapers/paper_files/AISTATS2010_NohZL10.pdf.

Noh, Yung-kyun, Byoung-tak Zhang, and Daniel D. Lee. “Generative Local Metric Learning for Nearest Neighbor Classification.” In Advances in Neural Information Processing Systems 23, edited by J. D. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, and A. Culotta, 1822–30. Curran Associates, Inc., 2010. http://papers.nips.cc/paper/4040-generative-local-metric-learning-for-nearest-neighbor-classification.pdf.

Ortega, Pedro A., and Daniel D. Lee. “An Adversarial Interpretation of Information-Theoretic Bounded Rationality.” In Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014. http://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/view/8550.

Ortega, Pedro, Kee-Eung Kim, and Daniel Lee. “Reactive Bandits with Attitude,” 726–34, 2015. http://jmlr.org/proceedings/papers/v38/ortega15.html.

Rubin, J., D. D. Lee, and H. Sompolinsky. “Equilibrium Properties of Temporally Asymmetric Hebbian Plasticity.” Phys. Rev. Lett. 86 (2001): 364–67.

Saul, L. K., F. Sha, and D. D. Lee. “Statistical Signal Processing with Nonnegativity Constraints.” In Proceedings of the Eighth European Conference on Speech Communication and Technology, Vol. 8, 2003.

Saul, Lawrence K., and Daniel D. Lee. “Multiplicative Updates for Classification by Mixture Models.” In Advances in Neural Information Processing Systems 14, edited by T. G. Dietterich, S. Becker, and Z. Ghahramani, 897–904. MIT Press, 2002. http://papers.nips.cc/paper/2085-multiplicative-updates-for-classification-by-mixture-models.pdf.

Saul, Lawrence K., Daniel D. Lee, Charles L. Isbell, and Yann L. Cun. “Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch.” In Advances in Neural Information Processing Systems 15, edited by S. Becker, S. Thrun, and K. Obermayer, 1205–12. MIT Press, 2003. http://papers.nips.cc/paper/2289-real-time-voice-processing-with-audiovisual-feedback-toward-autonomous-agents-with-perfect-pitch.pdf.

Seung, H. S., D. D. Lee, B. Y. Reis, and D. W. Tank. “Stability of the Memory of Eye Position in a Recurrent Network of Conductance-Based Model Neurons.” Neuron 26 (2000): 259–71.

———. “The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback.” J. Computational Neuroscience 9 (2000): 171–85.

Seung, H. Sebastian, and Daniel D. Lee. “The Manifold Ways of Perception.” Science 290, no. 5500 (12–22, 2000): 2268–69. doi:10.1126/science.290.5500.2268.

Seung-Joon Yi, Byoung-Tak Zhang, Dennis Hong, and Daniel D. Lee. “Learning Full Body Push Recovery Control for Small Humanoid Robots,” 2047–52. IEEE, 2011. doi:10.1109/ICRA.2011.5980531.

Sha, Fei, Lawrence K. Saul, and Daniel D. Lee. “Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines.” In Advances in Neural Information Processing Systems 15, edited by S. Becker, S. Thrun, and K. Obermayer, 1065–72. MIT Press, 2003. http://papers.nips.cc/paper/2280-multiplicative-updates-for-nonnegative-quadratic-programming-in-support-vector-machines.pdf.

Shriki, Oren, Haim Sompolinsky, and Daniel D. Lee. “An Information Maximization Approach to Overcomplete and Recurrent Representations.” In Advances in Neural Information Processing Systems 13, edited by T. K. Leen, T. G. Dietterich, and V. Tresp, 612–18. MIT Press, 2001. http://papers.nips.cc/paper/1863-an-information-maximization-approach-to-overcomplete-and-recurrent-representations.pdf.

Sinha, S.K., Y.P. Feng, C.A. Melendres, D.D. Lee, T.P. Russell, S.K. Satija, E.B. Sirota, and M.K. Sanyal. “Off-Specular X-Ray Scattering Studies of the Morphology of Thin Films.” Physica A: Statistical Mechanics and Its Applications 231, no. 1–3 (September 1996): 99–110. doi:10.1016/0378-4371(96)00085-4.

Socci, Nicholas D., Daniel D. Lee, and H. Sebastian Seung. “The Rectified Gaussian Distribution.” In Advances in Neural Information Processing Systems 10, edited by M. I. Jordan, M. J. Kearns, and S. A. Solla, 350–56. MIT Press, 1998. http://papers.nips.cc/paper/1402-the-rectified-gaussian-distribution.pdf.

Vernaza, P., and D.D. Lee. “Rao-Blackwellized Particle Filtering for 6-DOF Estimation of Attitude and Position via GPS and Inertial Sensors,” 1571–78. IEEE, 2006. doi:10.1109/ROBOT.2006.1641931.

Vernaza, P., M. Likhachev, S. Bhattacharya, S. Chitta, A. Kushleyev, and D.D. Lee. “Search-Based Planning for a Legged Robot over Rough Terrain,” 2380–87. IEEE, 2009. doi:10.1109/ROBOT.2009.5152769.

Vernaza, Paul, and Daniel D Lee. “Scalable Real-Time Object Recognition and Segmentation via Cascaded, Discriminative Markov Random Fields,” 3102–7. IEEE, 2010. doi:10.1109/ROBOT.2010.5509209.

Vernaza, Paul, Daniel D Lee, and Seung-Joon Yi. “Learning and Planning High-Dimensional Physical Trajectories via Structured Lagrangians,” 846–52. IEEE, 2010. doi:10.1109/ROBOT.2010.5509698.

Vernaza, Paul, and Daniel D. Lee. “Efficient Dynamic Programming for High-Dimensional, Optimal Motion Planning by Spectral Learning of Approximate Value Function Symmetries,” 6121–27. IEEE, 2011. doi:10.1109/ICRA.2011.5980552.

———. “Learning and Exploiting Low-Dimensional Structure for Efficient Holonomic Motion Planning in High-Dimensional Spaces.” The International Journal of Robotics Research 31, no. 14 (December 1, 2012): 1739–60. doi:10.1177/0278364912457436.

———. “Learning Dimensional Descent for Optimal Motion Planning in High-Dimensional Spaces.” In Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011. https://www.aaai.org/ocs/index.php/AAAI/AAAI11/paper/view/3748.

———. “Learning Dimensional Descent Planning for a Highly-Articulated Robot Arm,” 2186–91. IEEE, 2011. doi:10.1109/IROS.2011.6095009.

Vernaza, Paul, Ben Taskar, and Daniel D. Lee. “Online, Self-Supervised Terrain Classification via Discriminatively Trained Submodular Markov Random Fields,” 2750–57. IEEE, 2008. doi:10.1109/ROBOT.2008.4543627.

Wang, Zhuo, Alan Stocker, and Daniel Lee. “Optimal Neural Population Codes for High-Dimensional Stimulus Variables.” In Advances in Neural Information Processing Systems 26, edited by C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger, 297–305. Curran Associates, Inc., 2013. http://papers.nips.cc/paper/4994-optimal-neural-population-codes-for-high-dimensional-stimulus-variables.pdf.

———. “Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss.” In Advances in Neural Information Processing Systems 25, edited by F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger, 2168–76. Curran Associates, Inc., 2012. http://papers.nips.cc/paper/4783-optimal-neural-tuning-curves-for-arbitrary-stimulus-distributions-discrimax-infomax-and-minimum-l_p-loss.pdf.

White, Olivia L., Daniel D. Lee, and Haim Sompolinsky. “Short-Term Memory in Orthogonal Neural Networks.” Physical Review Letters 92, no. 14 (April 9, 2004): 148102. doi:10.1103/PhysRevLett.92.148102.

Yi, Seung-Joon, Dennis Hong, and Daniel D. Lee. “A Hybrid Walk Controller for Resource-Constrained Humanoid Robots,” 88–93. IEEE, 2013. doi:10.1109/HUMANOIDS.2013.7029960.

Yi, Seung-Joon, S. McGill, L. Vadakedathu, Qin He, Inyong Ha, M. Rouleau, D. Hong, and D.D. Lee. “Modular Low-Cost Humanoid Platform for Disaster Response.” In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), 965–72, 2014. doi:10.1109/IROS.2014.6942676.

Yi, Seung-Joon, S.G. McGill, Byoung-Tak Zhang, D. Hong, and D.D. Lee. “Active Stabilization of a Humanoid Robot for Real-Time Imitation of a Human Operator.” In 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 761–66, 2012. doi:10.1109/HUMANOIDS.2012.6651605.

Yi, Seung-Joon, Stephen G. McGill, Larry Vadakedathu, Qin He, Inyong Ha, Jeakweon Han, Hyunjong Song, et al. “Team THOR’s Entry in the DARPA Robotics Challenge Trials 2013.” Journal of Field Robotics, December 1, 2014, n/a – n/a. doi:10.1002/rob.21555.

Yi, Seung-Joon, Byoung-Tak Zhang, D. Hong, and D.D. Lee. “Online Learning of Low Dimensional Strategies for High-Level Push Recovery in Bipedal Humanoid Robots.” In 2013 IEEE International Conference on Robotics and Automation (ICRA), 1649–55, 2013. doi:10.1109/ICRA.2013.6630791.

Yi, Seung-Joon, Byoung-Tak Zhang, Dennis Hong, and Daniel D. Lee. “Active Stabilization of a Humanoid Robot for Impact Motions with Unknown Reaction Forces,” 4034–39. IEEE, 2012. doi:10.1109/IROS.2012.6385854.

———. “Online Learning of a Full Body Push Recovery Controller for Omnidirectional Walking,” 1–6. IEEE, 2011. doi:10.1109/Humanoids.2011.6100896.

———. “Practical Bipedal Walking Control on Uneven Terrain Using Surface Learning and Push Recovery,” 3963–68. IEEE, 2011. doi:10.1109/IROS.2011.6095131.

Yuanqing Lin, and D.D. Lee. “Bayesian L>inf<1>/inf<-Norm Sparse Learning,” 5:V – 605 – V – 608. IEEE, 2006. doi:10.1109/ICASSP.2006.1661348.

———. “Bayesian Regularization and Nonnegative Deconvolution (BRAND) for Acoustic Echo Cancellation,” 41–44. IEEE, 2005. doi:10.1109/ASPAA.2005.1540163.

———. “Bayesian Regularization and Nonnegative Deconvolution for Room Impulse Response Estimation.” IEEE Transactions on Signal Processing 54, no. 3 (March 2006): 839–47. doi:10.1109/TSP.2005.863030.

———. “Relevant Deconvolution for Acoustic Source Estimation,” 5:529–32. IEEE, 2005. doi:10.1109/ICASSP.2005.1416357.

Yuanqing Lin, D.D. Lee, and L.K. Saul. “Nonnegative Deconvolution for Time of Arrival Estimation,” 2:ii – 377–80. IEEE, 2004. doi:10.1109/ICASSP.2004.1326273.

Yung-Kyun Noh, Jihun Hamm, and Daniel D. Lee. “Regularized Discriminant Analysis for Transformation-Invariant Object Recognition,” 1–5. IEEE, 2008. doi:10.1109/ICPR.2008.4761378.

Yuta, Shin ’ichi, Daniel D. Lee, Keiji Nagatani, and Yasushi Nakauchi. “Preface.” Advanced Robotics 26, no. 14 (September 2012): 1537–38. doi:10.1080/01691864.2012.701601.