Unsupervised Learning by Convex and Conic Coding. - Daniel D. Lee; H. Sebastian Seung (NIPS, 1996)

A Neural Network Based Head Tracking System. - Daniel D. Lee; H. Sebastian Seung (NIPS, 1997)

The Rectified Gaussian Distribution. - Nicholas D. Socci; Daniel D. Lee; H. Sebastian Seung (NIPS, 1997)

Learning a Continuous Hidden Variable Model for Binary Data. - Daniel D. Lee; Haim Sompolinsky (NIPS, 1998)

Learning in Intelligent Embedded Systems. - Daniel D. Lee; H. Sebastian Seung (USENIX Workshop on Embedded Systems, 1999)

The Nonnegative Boltzmann Machine. - Oliver B. Downs; David J. C. MacKay; Daniel D. Lee (NIPS, 1999)

Algorithms for Independent Components Analysis and Higher Order Statistics. - Daniel D. Lee; Uri Rokni; Haim Sompolinsky (NIPS, 1999)

Algorithms for Non-negative Matrix Factorization. - Daniel D. Lee; H. Sebastian Seung (NIPS, 2000)

An Information Maximization Approach to Overcomplete and Recurrent Representations. - Oren Shriki; Haim Sompolinsky; Daniel D. Lee (NIPS, 2000)

The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback. - H. Sebastian Seung; Daniel D. Lee; Ben Y. Reis; David W. Tank (J. Comput. Neurosci., 2000)

Multiplicative Updates for Classification by Mixture Models. - Lawrence K. Saul; Daniel D. Lee (NIPS, 2001)

Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. - Lawrence K. Saul; Daniel D. Lee; Charles L. Isbell Jr.; Yann LeCun (NIPS, 2002)

Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. - Fei Sha; Lawrence K. Saul; Daniel D. Lee (NIPS, 2002)

Multiplicative Updates for Large Margin Classifiers. - Fei Sha; Lawrence K. Saul; Daniel D. Lee (COLT, 2003)

Biologically motivated computational models. - Mitra Basu; Jon Timmis; Dipankar Dasgupta; Daniel D. Lee; Guang R. Gao; Kwabena A. Boahen (IJCNN, 2003)

Statistical signal processing with nonnegativity constraints. - Lawrence K. Saul; Fei Sha; Daniel D. Lee (INTERSPEECH, 2003)

Nonnegative deconvolution for time of arrival estimation. - Yuanqing Lin; Daniel D. Lee; Lawrence K. Saul (ICASSP (2), 2004)

A kernel view of the dimensionality reduction of manifolds. - Jihun Ham; Daniel D. Lee; Sebastian Mika; Bernhard Schölkopf (ICML, 2004)

Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation. - Yuanqing Lin; Daniel D. Lee (NIPS, 2004)

Semisupervised alignment of manifolds. - Jihun Ham; Daniel D. Lee; Lawrence K. Saul (AISTATS, 2005)

Relevant deconvolution for acoustic source estimation. - Yuanqing Lin; Daniel D. Lee (ICASSP (5), 2005)

Learning nonlinear appearance manifolds for robot localization. - Jihun Ham; Yuanqing Lin; Daniel D. Lee (IROS, 2005)

Cooperative relative robot localization with audible acoustic sensing. - Yuanqing Lin; Paul Vernaza; Jihun Ham; Daniel D. Lee (IROS, 2005)

Spectral Methods for Dimensionality Reduction. - Lawrence K. Saul; Kilian Q. Weinberger; Fei Sha; Jihun Ham; Daniel D. Lee (Semi-Supervised Learning, 2006)

Learning a manifold-constrained map between image sets: applications to matching and pose estimation. - Jihun Ham; Ikkjin Ahn; Daniel D. Lee (CVPR (1), 2006)

Room Impulse Response Estimation using Sparse Online Prediction and Absolute Loss. - Koby Crammer; Daniel D. Lee (ICASSP (3), 2006)

Bayesian L1-Norm Sparse Learning. - Yuanqing Lin; Daniel D. Lee (ICASSP (5), 2006)

Rao-Blackwellized Particle Filtering for 6-DOF Estimation of Attitude and Position via GPS and Inertial Sensors. - Paul Vernaza; Daniel D. Lee (ICRA, 2006)

Robust GPS/INS-Aided Localization and Mapping Via GPS Bias Estimation. - Paul Vernaza; Daniel D. Lee (ISER, 2006)

Bayesian regularization and nonnegative deconvolution for room impulse response estimation. - Yuanqing Lin; Daniel D. Lee (IEEE Trans. Signal Process., 2006)

Proprioceptive localilzatilon for a quadrupedal robot on known terrain. - Sachin Chitta; Paul Vemaza; Roman Geykhman; Daniel D. Lee (ICRA, 2007)

Blind channel identification for speech dereverberation using l1-norm sparse learning. - Yuanqing Lin; Jingdong Chen; Youngmoo E. Kim; Daniel D. Lee (NIPS, 2007)

Multiplicative Updates for Nonnegative Quadratic Programming. - Fei Sha; Yuanqing Lin; Lawrence K. Saul; Daniel D. Lee (Neural Comput., 2007)

Grassmann discriminant analysis: a unifying view on subspace-based learning. - Jihun Ham; Daniel D. Lee (ICML, 2008)

Regularized discriminant analysis for transformation-invariant object recognition. - Yung-Kyun Noh; Jihun Ham; Daniel D. Lee (ICPR, 2008)

Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields. - Paul Vernaza; Ben Taskar; Daniel D. Lee (ICRA, 2008)

Extended Grassmann Kernels for Subspace-Based Learning. - Jihun Ham; Daniel D. Lee (NIPS, 2008)

Learning a Warped Subspace Model of Faces with Images of Unknown Pose and Illumination. - Jihun Ham; Daniel D. Lee (VISAPP (1), 2008)

Little Ben: The Ben Franklin Racing Team's entry in the 2007 DARPA Urban Challenge. - Jonathan Bohren; Tully Foote; Jim Keller 002; Alex Kushleyev; Daniel D. Lee; Alex Stewart; Paul Vernaza; Jason C. Derenick; John R. Spletzer; Brian Satterfield (J. Field Robotics, 2008)

Search-based planning for a legged robot over rough terrain. - Paul Vernaza; Maxim Likhachev; Subhrajit Bhattacharya; Sachin Chitta; Aleksandr Kushleyev; Daniel D. Lee (ICRA, 2009)

Learning Sparse Markov Network Structure via Ensemble-of-Trees Models. - Yuanqing Lin; Shenghuo Zhu; Daniel D. Lee; Ben Taskar (AISTATS, 2009)

Online Learning of Uneven Terrain for Humanoid Bipedal Walking. - Seung-Joon Yi; Byoung-Tak Zhang; Daniel D. Lee (AAAI, 2010)

Scalable real-time object recognition and segmentation via cascaded, discriminative Markov random fields. - Paul Vernaza; Daniel D. Lee (ICRA, 2010)

Learning and planning high-dimensional physical trajectories via structured Lagrangians. - Paul Vernaza; Daniel D. Lee; Seung-Joon Yi (ICRA, 2010)

Learning via Gaussian Herding. - Koby Crammer; Daniel D. Lee (NIPS, 2010)

Fluid Dynamics Models for Low Rank Discriminant Analysis. - Yung-Kyun Noh; Byoung-Tak Zhang; Daniel D. Lee (AISTATS, 2010)

Learning Dimensional Descent for Optimal Motion Planning in High-dimensional Spaces. - Paul Vernaza; Daniel D. Lee (AAAI, 2011)

Cooperative humanoid stretcher manipulation and locomotion. - Stephen G. McGill; Daniel D. Lee (Humanoids, 2011)

Online learning of a full body push recovery controller for omnidirectional walking. - Seung-Joon Yi; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (Humanoids, 2011)

Efficient dynamic programming for high-dimensional, optimal motion planning by spectral learning of approximate value function symmetries. - Paul Vernaza; Daniel D. Lee (ICRA, 2011)

Learning full body push recovery control for small humanoid robots. - Seung-Joon Yi; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (ICRA, 2011)

Learning Dimensional Descent planning for a highly-articulated robot arm. - Paul Vernaza; Daniel D. Lee (IROS, 2011)

Practical bipedal walking control on uneven terrain using surface learning and push recovery. - Seung-Joon Yi; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (IROS, 2011)

RoboCup 2011 Humanoid League Winners. - Daniel D. Lee; Seung-Joon Yi; Stephen G. McGill; Yida Zhang; Sven Behnke; Marcell Missura; Hannes Schulz; Dennis W. Hong; Jeakweon Han; Michael A. Hopkins (RoboCup, 2011)

Learning Discriminative Metrics via Generative Models and Kernel Learning - Yuan Shi; Yung-Kyun Noh; Fei Sha; Daniel D. Lee (CoRR, 2011)

Active stabilization of a humanoid robot for real-time imitation of a human operator. - Seung-Joon Yi; Stephen G. McGill; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (Humanoids, 2012)

Online discriminative learning of phoneme recognition via collections of generalized linear models. - Koby Crammer; Daniel D. Lee (ICASSP, 2012)

Active stabilization of a humanoid robot for impact motions with unknown reaction forces. - Seung-Joon Yi; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (IROS, 2012)

Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification. - Yung-Kyun Noh; Frank Chongwoo Park; Daniel D. Lee (NIPS, 2012)

"Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss". - Zhuo Wang; Alan A. Stocker; Daniel D. Lee (NIPS, 2012)

Sensor Information Processing in Robot Competitions and Real World Robotic Challenges. - Keiji Nagatani; Alex Kushleyev; Daniel D. Lee (Adv. Robotics, 2012)

Preface. - Shin'ichi Yuta; Daniel D. Lee; Keiji Nagatani; Yasushi Nakauchi (Adv. Robotics, 2012)

Learning and exploiting low-dimensional structure for efficient holonomic motion planning in high-dimensional spaces. - Paul Vernaza; Daniel D. Lee (Int. J. Robotics Res., 2012)

The University of Pennsylvania MAGIC 2010 multi-robot unmanned vehicle system. - Jonathan Butzke; Kostas Daniilidis; Aleksandr Kushleyev; Daniel D. Lee; Maxim Likhachev; Cody J. Phillips 001; Mike Phillips (J. Field Robotics, 2012)

k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling. - Yung-Kyun Noh; Frank Chongwoo Park; Daniel D. Lee (CogSci, 2013)

A hybrid walk controller for resource-constrained humanoid robots. - Seung-Joon Yi; Dennis W. Hong; Daniel D. Lee (Humanoids, 2013)

Online learning of low dimensional strategies for high-level push recovery in bipedal humanoid robots. - Seung-Joon Yi; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (ICRA, 2013)

Optimal Neural Population Codes for High-dimensional Stimulus Variables. - Zhuo Wang; Alan A. Stocker; Daniel D. Lee (NIPS, 2013)

RoboCup 2013 Humanoid Kidsize League Winner. - Daniel D. Lee; Seung-Joon Yi; Stephen G. McGill; Yida Zhang; Larry Vadakedathu; Samarth Brahmbhatt; Richa Agrawal; Vibhavari Dasagi (RoboCup, 2013)

Extensions of a RoboCup Soccer Software Framework. - Stephen G. McGill; Seung-Joon Yi; Yida Zhang; Daniel D. Lee (RoboCup, 2013)

An Adversarial Interpretation of Information-Theoretic Bounded Rationality. - Pedro A. Ortega; Daniel D. Lee (AAAI, 2014)

Estimating manipulability of unknown obstacles for navigation in indoor environments. - Christopher Clingerman; Daniel D. Lee (ICRA, 2014)

Modular low-cost humanoid platform for disaster response. - Seung-Joon Yi; Stephen G. McGill; Larry Vadakedathu; Qin He; Inyong Ha; Michael Rouleau; Dennis W. Hong; Daniel D. Lee (IROS, 2014)

An application of parametric speaker technology to bus-pedestrian collision warning. - Alexander Burka; Alaric Qin; Daniel D. Lee (ITSC, 2014)

RoboCup 2014 Humanoid AdultSize League Winner. - Seung-Joon Yi; Steve McGill; Qin He; Larry Vadakedathu; Hak Yi; Sanghyun Cho; Dennis W. Hong; Daniel D. Lee (RoboCup, 2014)

THOR-OP humanoid robot for DARPA Robotics Challenge Trials 2013. - Seung-Joon Yi; Stephen G. McGill; Larry Vadakedathu; Qin He; Inyong Ha; Jeakweon Han; Hyunjong Song; Michael Rouleau; Dennis W. Hong; Daniel D. Lee (URAI, 2014)

Reactive bandits with attitude. - Pedro A. Ortega; Kee-Eung Kim; Daniel D. Lee (AISTATS, 2015)

Causal reasoning in a prediction task with hidden causes. - Pedro A. Ortega; Daniel D. Lee; Alan A. Stocker (CogSci, 2015)

Team THOR's adaptive autonomy for disaster response humanoids. - Stephen G. McGill; Seung-Joon Yi; Daniel D. Lee (Humanoids, 2015)

Heel and toe lifting walk controller for traversing uneven terrain. - Seung-Joon Yi; Dennis W. Hong; Daniel D. Lee (Humanoids, 2015)

Online self-supervised monocular visual odometry for ground vehicles. - Bhoram Lee; Kostas Daniilidis; Daniel D. Lee (ICRA, 2015)

Dynamic and probabilistic estimation of manipulable obstacles for indoor navigation. - Christopher Clingerman; Peter J. Wei; Daniel D. Lee (IROS, 2015)

Belief flows for robust online learning. - Pedro A. Ortega; Koby Crammer; Daniel D. Lee (ITA, 2015)

RoboCup 2015 Humanoid AdultSize League Winner. - Seung-Joon Yi; Stephen G. McGill; Heejin Jeong; Jinwook Huh; Marcell Missura; Hak Yi; Min Sung Ahn; Sanghyun Cho; Kevin Liu; Dennis W. Hong; Daniel D. Lee (RoboCup, 2015)

Molecular learning with DNA kernel machines. - Yung-Kyun Noh; Daniel D. Lee; Kyung-Ae Yang; Cheong-Tag Kim; Byoung-Tak Zhang (Biosyst., 2015)

The Stan Math Library: Reverse-Mode Automatic Differentiation in C++. - Bob Carpenter; Matthew D. Hoffman; Marcus A. Brubaker; Daniel D. Lee; Peter Li; Michael Betancourt (CoRR, 2015)

Classification of Manifolds by Single-Layer Neural Networks. - SueYeon Chung; Daniel D. Lee; Haim Sompolinsky (CoRR, 2015)

Team THOR's Entry in the DARPA Robotics Challenge Trials 2013. - Seung-Joon Yi; Stephen G. McGill; Larry Vadakedathu; Qin He; Inyong Ha; Jeakweon Han; Hyunjong Song; Michael Rouleau; Byoung-Tak Zhang; Dennis W. Hong; Mark Yim; Daniel D. Lee (J. Field Robotics, 2015)

Learning Complex Stand-Up Motion for Humanoid Robots. - Heejin Jeong; Daniel D. Lee (AAAI, 2016)

Dynamic heel-strike toe-off walking controller for full-size modular humanoid robots. - Seung-Joon Yi; Daniel D. Lee (Humanoids, 2016)

Learning high-dimensional Mixture Models for fast collision detection in Rapidly-Exploring Random Trees. - Jinwook Huh; Daniel D. Lee (ICRA, 2016)

Learning anisotropic ICP (LA-ICP) for robust and efficient 3D registration. - Bhoram Lee; Daniel D. Lee (ICRA, 2016)

Low dimensional human preference tracking for motion optimization. - Stephen G. McGill; Seung-Joon Yi; Daniel D. Lee (ICRA, 2016)

Bayesian Reinforcement Learning with Behavioral Feedback. - Teakgyu Hong; Jongmin Lee 004; Kee-Eung Kim; Pedro A. Ortega; Daniel D. Lee (IJCAI, 2016)

Efficient learning of stand-up motion for humanoid robots with bilateral symmetry. - Heejin Jeong; Daniel D. Lee (IROS, 2016)

Online learning of visibility and appearance for object pose estimation. - Bhoram Lee; Daniel D. Lee (IROS, 2016)

Heel and toe lifting walk controller for resource constrained humanoid robots. - Seung-Joon Yi; Daniel D. Lee (IROS, 2016)

Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution. - Christopher Lynn; Daniel D. Lee (NIPS, 2016)

Efficient Neural Codes under Metabolic Constraints. - Zhuo Wang; Xue-Xin Wei; Alan A. Stocker; Daniel D. Lee (NIPS, 2016)

Adaptive Field Detection and Localization in Robot Soccer. - Yongbo Qian; Daniel D. Lee (RoboCup, 2016)

Whole-Body Balancing Walk Controller for Position Controlled Humanoid Robots. - Seung-Joon Yi; Byoung-Tak Zhang; Dennis W. Hong; Daniel D. Lee (Int. J. Humanoid Robotics, 2016)

Efficient Neural Codes That Minimize Lp Reconstruction Error. - Zhuo Wang; Alan A. Stocker; Daniel D. Lee (Neural Comput., 2016)

Robot Learning. - Jan Peters 001; Daniel D. Lee; Jens Kober; Duy Nguyen-Tuong; J. Andrew Bagnell; Stefan Schaal (Springer Handbook of Robotics, 2nd Ed., 2016)

Adaptive motion planning with high-dimensional mixture models. - Jinwook Huh; Bhoram Lee; Daniel D. Lee (ICRA, 2017)

Artificial invariant subspace with potential functions for humanoid robot balancing. - Xiang Deng; Fei Miao; Daniel D. Lee (IROS, 2017)

Self-supervised online learning of appearance for 3D tracking. - Bhoram Lee; Daniel D. Lee (IROS, 2017)

The synchronized holonomic model: A framework for efficient generation of motion. - Marcell Missura; Daniel D. Lee; Oskar von Stryk; Maren Bennewitz (IROS, 2017)

Generative Local Metric Learning for Kernel Regression. - Yung-Kyun Noh; Masashi Sugiyama; Kee-Eung Kim; Frank C. Park 001; Daniel D. Lee (NIPS, 2017)

Neural Network Memory Architectures for Autonomous Robot Navigation. - Steven W. Chen; Nikolay Atanasov 001; Arbaaz Khan; Konstantinos Karydis; Daniel D. Lee; Vijay Kumar 001 (CoRR, 2017)

End-to-End Navigation in Unknown Environments using Neural Networks. - Arbaaz Khan; Clark Zhang; Nikolay Atanasov 001; Konstantinos Karydis; Daniel D. Lee; Vijay Kumar 001 (CoRR, 2017)

Classification and Geometry of General Perceptual Manifolds. - SueYeon Chung; Daniel D. Lee; Haim Sompolinsky (CoRR, 2017)

Team THOR's Entry in the DARPA Robotics Challenge Finals 2015. - Stephen G. McGill; Seung-Joon Yi; Hak Yi; Min Sung Ahn; Sanghyun Cho; Kevin Liu; Daniel Sun 002; Bhoram Lee; Heejin Jeong; Jinwook Huh; Dennis W. Hong; Daniel D. Lee (J. Field Robotics, 2017)

Maximizing Activity in Ising Networks via the TAP Approximation. - Christopher W. Lynn; Daniel D. Lee (AAAI, 2018)

Bayesian Q-learning with Assumed Density Filtering. - Heejin Jeong; Daniel D. Lee (AAAI Spring Symposia, 2018)

Online Deep Learning in Wireless Communication Systems. - Mark Eisen; Clark Zhang; Luiz F. O. Chamon; Daniel D. Lee; Alejandro Ribeiro (ACSSC, 2018)

Approximating Explicit Model Predictive Control Using Constrained Neural Networks. - Steven W. Chen; Kelsey Saulnier; Nikolay Atanasov 001; Daniel D. Lee; Vijay Kumar 001; George J. Pappas; Manfred Morari (ACC, 2018)

Memory Augmented Control Networks. - Arbaaz Khan; Clark Zhang; Nikolay Atanasov 001; Konstantinos Karydis; Vijay Kumar 001; Daniel D. Lee (ICLR (Poster), 2018)

Constrained Sampling-Based Planning for Grasping and Manipulation. - Jinwook Huh; Bhoram Lee; Daniel D. Lee (ICRA, 2018)

Artificial Invariant Subspace for Humanoid Robot Balancing in Locomotion. - Xiang Deng; Daniel D. Lee (IROS, 2018)

Minimal Construct: Efficient Shortest Path Finding for Mobile Robots in Polygonal Maps. - Marcell Missura; Daniel D. Lee; Maren Bennewitz (IROS, 2018)

Learning Implicit Sampling Distributions for Motion Planning. - Clark Zhang; Jinwook Huh; Daniel D. Lee (IROS, 2018)

Surges of collective human activity emerge from simple pairwise correlations. - Christopher W. Lynn; Lia Papadopoulos; Daniel D. Lee; Danielle S. Bassett (CoRR, 2018)

Nearest neighbor density functional estimation based on inverse Laplace transform. - Shouvik Ganguly; Jongha Ryu; Young-Han Kim 001; Yung-Kyun Noh; Daniel D. Lee (CoRR, 2018)

Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients. - Arbaaz Khan; Clark Zhang; Daniel D. Lee; Vijay Kumar 001; Alejandro Ribeiro (CoRR, 2018)

U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification. - Ty Nguyen; Tolga Özaslan; Ian D. Miller; James Keller 002; Giuseppe Loianno; Camillo J. Taylor; Daniel D. Lee; Vijay Kumar 001; Joseph H. Harwood; Jennifer M. Wozencraft (CoRR, 2018)

Learning Data Manifolds with a Cutting Plane Method. - SueYeon Chung; Uri Cohen; Haim Sompolinsky; Daniel D. Lee (Neural Comput., 2018)

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. - Yung-Kyun Noh; Masashi Sugiyama; Song Liu 002; Marthinus Christoffel du Plessis; Frank Chongwoo Park; Daniel D. Lee (Neural Comput., 2018)

Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis. - Yung-Kyun Noh; Jihun Hamm; Frank Chongwoo Park; Byoung-Tak Zhang; Daniel D. Lee (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Generative Local Metric Learning for Nearest Neighbor Classification. - Yung-Kyun Noh; Byoung-Tak Zhang; Daniel D. Lee (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Efficient Sampling With Q-Learning to Guide Rapidly Exploring Random Trees. - Jinwook Huh; Daniel D. Lee (IEEE Robotics Autom. Lett., 2018)

Dual Domain Learning of Optimal Resource Allocations in Wireless Systems. - Mark Eisen; Clark Zhang; Luiz F. O. Chamon; Daniel D. Lee; Alejandro Ribeiro (ICASSP, 2019)

Online Continuous Mapping using Gaussian Process Implicit Surfaces. - Bhoram Lee; Clark Zhang; Zonghao Huang; Daniel D. Lee (ICRA, 2019)

Assumed Density Filtering Q-learning. - Heejin Jeong; Clark Zhang; George J. Pappas; Daniel D. Lee (IJCAI, 2019)

Learning Q-network for Active Information Acquisition. - Heejin Jeong; Brent Schlotfeldt; Hamed Hassani; Manfred Morari; Daniel D. Lee; George J. Pappas (IROS, 2019)

Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. - Tarik Tosun; Eric Mitchell; Ben Eisner; Jinwook Huh; Bhoram Lee; Daewon Lee; Volkan Isler; H. Sebastian Seung; Daniel D. Lee (IROS, 2019)

Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. - Jinwook Huh; Ömür Arslan; Daniel D. Lee (ISRR, 2019)

Q-Learning for Continuous Actions with Cross-Entropy Guided Policies. - Riley Simmons-Edler; Ben Eisner; Eric Mitchell; H. Sebastian Seung; Daniel D. Lee (CoRR, 2019)

QXplore: Q-learning Exploration by Maximizing Temporal Difference Error. - Riley Simmons-Edler; Ben Eisner; Eric Mitchell; H. Sebastian Seung; Daniel D. Lee (CoRR, 2019)

Bayesian optimistic Kullback-Leibler exploration. - Kanghoon Lee; Geon-hyeong Kim; Pedro A. Ortega; Daniel D. Lee; Kee-Eung Kim (Mach. Learn., 2019)

RoboCup: A Treasure Trove of Rich Diversity for Research Issues and Interdisciplinary Connections [TC Spotlight]. - Minoru Asada; Peter Stone 001; Manuela Veloso; Daniel D. Lee; Daniele Nardi (IEEE Robotics Autom. Mag., 2019)

Learning Optimal Resource Allocations in Wireless Systems. - Mark Eisen; Clark Zhang; Luiz F. O. Chamon; Daniel D. Lee; Alejandro Ribeiro (IEEE Trans. Signal Process., 2019)

Jointly Learning Visual Motion and Confidence from Local Patches in Event Cameras. - Daniel R. Kepple; Daewon Lee; Colin Prepsius; Volkan Isler; Il Memming Park; Daniel D. Lee (ECCV (6), 2020)

On-Device Event Filtering with Binary Neural Networks for Pedestrian Detection Using Neuromorphic Vision Sensors. - Fernando Cladera Ojeda; Anthony Bisulco; Daniel R. Kepple; Volkan Isler; Daniel D. Lee (ICIP, 2020)

Surface Hof: Surface Reconstruction From A Single Image Using Higher Order Function Networks. - Ziyun Wang 001; Volkan Isler; Daniel D. Lee (ICIP, 2020)

Higher-Order Function Networks for Learning Composable 3D Object Representations. - Eric Mitchell; Selim Engin; Volkan Isler; Daniel D. Lee (ICLR, 2020)

Higher Order Function Networks for View Planning and Multi-View Reconstruction. - Selim Engin; Eric Mitchell; Daewon Lee; Volkan Isler; Daniel D. Lee (ICRA, 2020)

Reward Prediction Error as an Exploration Objective in Deep RL. - Riley Simmons-Edler; Ben Eisner; Daniel Yang; Anthony Bisulco; Eric Mitchell; H. Sebastian Seung; Daniel D. Lee (IJCAI, 2020)

Acoustic Collision Detection and Localization for Robot Manipulators. - Xiaoran Fan; Daewon Lee; Yuan Chen 006; Colin Prepscius; Volkan Isler; Larry D. Jackel; H. Sebastian Seung; Daniel D. Lee (IROS, 2020)

Learning to Generate Cost-to-Go Functions for Efficient Motion Planning. - Jinwook Huh; Galen Xing; Ziyun Wang 001; Volkan Isler; Daniel D. Lee (ISER, 2020)

Near-Chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection. - Anthony Bisulco; Fernando Cladera Ojeda; Volkan Isler; Daniel Dongyuel Lee (ISVLSI, 2020)

Learning to Track Dynamic Targets in Partially Known Environments. - Heejin Jeong; Hamed Hassani; Manfred Morari; Daniel D. Lee; George J. Pappas (CoRR, 2020)

Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems. - Niko A. Grupen; Daniel D. Lee; Bart Selman (CoRR, 2020)

Geodesic-HOF: 3D Reconstruction Without Cutting Corners. - Ziyun Wang 001; Eric A. Mitchell; Volkan Isler; Daniel D. Lee (AAAI, 2021)

Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors. - Anthony Bisulco; Fernando Cladera Ojeda; Volkan Isler; Daniel D. Lee (ICRA, 2021)

Cost-to-Go Function Generating Networks for High Dimensional Motion Planning. - Jinwook Huh; Volkan Isler; Daniel D. Lee (ICRA, 2021)

Deep Reinforcement Learning for Active Target Tracking. - Heejin Jeong; Hamed Hassani; Manfred Morari; Daniel D. Lee; George J. Pappas (ICRA, 2021)

Occupancy Map Inpainting for Online Robot Navigation. - Minghan Wei; Daewon Lee; Volkan Isler; Daniel D. Lee (ICRA, 2021)

Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction. - Daniel Yang; Tarik Tosun; Benjamin Eisner; Volkan Isler; Daniel D. Lee (ICRA, 2021)

AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection. - Xiaoran Fan; Riley Simmons-Edler; Daewon Lee; Larry D. Jackel; Richard E. Howard; Daniel D. Lee (IROS, 2021)

Learning Continuous Cost-to-Go Functions for Non-holonomic Systems. - Jinwook Huh; Daniel D. Lee; Volkan Isler (IROS, 2021)

Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization. - Travers Rhodes; Daniel D. Lee (NeurIPS, 2021)

Local Disentanglement in Variational Auto-Encoders Using Jacobian L1 Regularization. - Travers Rhodes; Daniel D. Lee (CoRR, 2021)

Fairness for Cooperative Multi-Agent Learning with Equivariant Policies. - Niko A. Grupen; Bart Selman; Daniel D. Lee (CoRR, 2021)

Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork. - Niko A. Grupen; Daniel D. Lee; Bart Selman (CoRR, 2021)

Object Shell Reconstruction: Camera-centric Object Representation for Robotic Grasping. - Nikhil Chavan Dafle; Sergiy Popovych; Shubham Agrawal; Daniel D. Lee; Volkan Isler (CoRR, 2021)

Tactile Velocity Estimation for Controlled In-Grasp Sliding. - Yuan Chen 006; Colin Prepscius; Daewon Lee; Daniel D. Lee (IEEE Robotics Autom. Lett., 2021)

Cooperative Multi-Agent Fairness and Equivariant Policies. - Niko A. Grupen; Bart Selman; Daniel D. Lee (AAAI, 2022)

Multi-Agent Curricula and Emergent Implicit Signaling. - Niko A. Grupen; Daniel D. Lee; Bart Selman (AAMAS, 2022)

Simultaneous Object Reconstruction and Grasp Prediction using a Camera-centric Object Shell Representation. - Nikhil Chavan Dafle; Sergiy Popovych; Shubham Agrawal; Daniel D. Lee; Volkan Isler (IROS, 2022)

Learning from Demonstration using a Curvature Regularized Variational Auto-Encoder (CurvVAE). - Travers Rhodes; Tapomayukh Bhattacharjee; Daniel D. Lee (IROS, 2022)

A theory of learning with constrained weight-distribution. - Weishun Zhong; Ben Sorscher; Daniel D. Lee; Haim Sompolinsky (CoRR, 2022)

Enabling Low-Cost Full Surface Tactile Skin for Human Robot Interaction. - Xiaoran Fan; Daewon Lee; Larry D. Jackel; Richard E. Howard; Daniel Dongyuel Lee; Volkan Isler (IEEE Robotics Autom. Lett., 2022)

EV-Catcher: High-Speed Object Catching Using Low-Latency Event-Based Neural Networks. - Ziyun Wang 001; Fernando Cladera Ojeda; Anthony Bisulco; Daewon Lee; Camillo J. Taylor; Kostas Daniilidis; M. Ani Hsieh; Daniel D. Lee; Volkan Isler (IEEE Robotics Autom. Lett., 2022)

Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. - J. Jon Ryu; Shouvik Ganguly; Younghan Kim 001; Yung-Kyun Noh; Daniel D. Lee (IEEE Trans. Inf. Theory, 2022)

AmbiSense: Acoustic Field Based Blindspot-Free Proximity Detection and Bearing Estimation. - Siddharth Rupavatharam; Xiaoran Fan; Caleb Escobedo; Daewon Lee; Larry D. Jackel; Richard E. Howard; Colin Prepscius; Daniel D. Lee; Volkan Isler (IROS, 2023)

Policy-Value Alignment and Robustness in Search-based Multi-Agent Learning. - Niko A. Grupen; Michael Hanlon; Alexis Hao; Daniel D. Lee; Bart Selman (CoRR, 2023)

Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks. - Chanwoo Chun; Daniel D. Lee (CoRR, 2023)

TimewarpVAE: Simultaneous Time-Warping and Representation Learning of Trajectories. - Travers Rhodes; Daniel D. Lee (CoRR, 2023)

Sparse Activations with Correlated Weights in Cortex-Inspired Neural Networks. - Chanwoo Chun; Daniel D. Lee (CPAL, 2024)

Parametric Matrix Models. - Patrick Cook; Danny Jammooa; Morten Hjorth-Jensen; Daniel D. Lee; Dean Lee (CoRR, 2024)

Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices. - Chanwoo Chun; SueYeon Chung; Daniel D. Lee (AISTATS, 2025)