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Daniel Dongyuel Lee
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- affiliation: University of Pennsylvania, Department of Electrical and Systems Engineering
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2020 – today
- 2024
[i47]Patrick Cook
, Danny Jammooa, Morten Hjorth-Jensen, Daniel D. Lee, Dean Lee:
Parametric Matrix Models. CoRR abs/2401.11694 (2024)- 2023
- [c131]Siddharth Rupavatharam, Xiaoran Fan, Caleb Escobedo, Daewon Lee, Larry D. Jackel, Richard E. Howard, Colin Prepscius, Daniel D. Lee, Volkan Isler:
AmbiSense: Acoustic Field Based Blindspot-Free Proximity Detection and Bearing Estimation. IROS 2023: 5974-5981 - [i46]Niko A. Grupen, Michael Hanlon, Alexis Hao, Daniel D. Lee, Bart Selman:
Policy-Value Alignment and Robustness in Search-based Multi-Agent Learning. CoRR abs/2301.11857 (2023) - [i45]Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis, M. Ani Hsieh, Daniel D. Lee, Volkan Isler:
EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks. CoRR abs/2304.07200 (2023) - [i44]Chanwoo Chun, Daniel D. Lee:
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks. CoRR abs/2305.10550 (2023) - [i43]Travers Rhodes, Daniel D. Lee:
TimewarpVAE: Simultaneous Time-Warping and Representation Learning of Trajectories. CoRR abs/2310.16027 (2023) - 2022
- [j25]Xiaoran Fan, Daewon Lee, Larry D. Jackel, Richard E. Howard, Daniel Dongyuel Lee, Volkan Isler:
Enabling Low-Cost Full Surface Tactile Skin for Human Robot Interaction. IEEE Robotics Autom. Lett. 7(2): 1800-1807 (2022) - [j24]Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis, M. Ani Hsieh, Daniel D. Lee, Volkan Isler:
EV-Catcher: High-Speed Object Catching Using Low-Latency Event-Based Neural Networks. IEEE Robotics Autom. Lett. 7(4): 8737-8744 (2022) - [j23]J. Jon Ryu, Shouvik Ganguly, Younghan Kim, Yung-Kyun Noh, Daniel D. Lee:
Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. IEEE Trans. Inf. Theory 68(6): 3511-3551 (2022) - [c130]Niko A. Grupen, Bart Selman, Daniel D. Lee:
Cooperative Multi-Agent Fairness and Equivariant Policies. AAAI 2022: 9350-9359 - [c129]Niko A. Grupen, Daniel D. Lee, Bart Selman:
Multi-Agent Curricula and Emergent Implicit Signaling. AAMAS 2022: 553-561 - [c128]Nikhil Chavan Dafle, Sergiy Popovych, Shubham Agrawal, Daniel D. Lee, Volkan Isler:
Simultaneous Object Reconstruction and Grasp Prediction using a Camera-centric Object Shell Representation. IROS 2022: 1396-1403 - [c127]Travers Rhodes, Tapomayukh Bhattacharjee, Daniel D. Lee:
Learning from Demonstration using a Curvature Regularized Variational Auto-Encoder (CurvVAE). IROS 2022: 10795-10800 - [i42]Weishun Zhong, Ben Sorscher, Daniel D. Lee, Haim Sompolinsky:
A theory of learning with constrained weight-distribution. CoRR abs/2206.08933 (2022) - 2021
- [j22]Yuan Chen, Colin Prepscius, Daewon Lee, Daniel D. Lee:
Tactile Velocity Estimation for Controlled In-Grasp Sliding. IEEE Robotics Autom. Lett. 6(2): 1614-1621 (2021) - [c126]Ziyun Wang, Eric A. Mitchell, Volkan Isler, Daniel D. Lee:
Geodesic-HOF: 3D Reconstruction Without Cutting Corners. AAAI 2021: 2844-2851 - [c125]Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Deep Reinforcement Learning for Active Target Tracking. ICRA 2021: 1825-1831 - [c124]Daniel Yang, Tarik Tosun, Benjamin Eisner, Volkan Isler, Daniel D. Lee:
Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction. ICRA 2021: 6350-6356 - [c123]Jinwook Huh, Volkan Isler, Daniel D. Lee:
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning. ICRA 2021: 8480-8486 - [c122]Minghan Wei, Daewon Lee, Volkan Isler, Daniel D. Lee:
Occupancy Map Inpainting for Online Robot Navigation. ICRA 2021: 8551-8557 - [c121]Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee:
Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors. ICRA 2021: 14098-14104 - [c120]Xiaoran Fan, Riley Simmons-Edler, Daewon Lee, Larry D. Jackel, Richard E. Howard, Daniel D. Lee:
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection. IROS 2021: 1763-1770 - [c119]Jinwook Huh, Daniel D. Lee, Volkan Isler:
Learning Continuous Cost-to-Go Functions for Non-holonomic Systems. IROS 2021: 5772-5779 - [c118]Travers Rhodes, Daniel D. Lee:
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization. NeurIPS 2021: 22708-22719 - [i41]Jinwook Huh, Daniel D. Lee, Volkan Isler:
Learning Continuous Cost-to-Go Functions for Non-holonomic Systems. CoRR abs/2103.11168 (2021) - [i40]Travers Rhodes, Daniel D. Lee:
Local Disentanglement in Variational Auto-Encoders Using Jacobian L1 Regularization. CoRR abs/2106.02923 (2021) - [i39]Niko A. Grupen, Bart Selman, Daniel D. Lee:
Fairness for Cooperative Multi-Agent Learning with Equivariant Policies. CoRR abs/2106.05727 (2021) - [i38]Niko A. Grupen, Daniel D. Lee, Bart Selman:
Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork. CoRR abs/2106.11156 (2021) - [i37]Xiaoran Fan, Riley Simmons-Edler, Daewon Lee, Larry D. Jackel, Richard E. Howard, Daniel D. Lee:
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection. CoRR abs/2108.04867 (2021) - [i36]Nikhil Chavan Dafle, Sergiy Popovych, Shubham Agrawal, Daniel D. Lee, Volkan Isler:
Object Shell Reconstruction: Camera-centric Object Representation for Robotic Grasping. CoRR abs/2109.06837 (2021) - 2020
- [c117]Daniel R. Kepple, Daewon Lee, Colin Prepsius, Volkan Isler, Il Memming Park, Daniel D. Lee:
Jointly Learning Visual Motion and Confidence from Local Patches in Event Cameras. ECCV (6) 2020: 500-516 - [c116]Ziyun Wang, Volkan Isler, Daniel D. Lee:
Surface Hof: Surface Reconstruction From A Single Image Using Higher Order Function Networks. ICIP 2020: 2666-2670 - [c115]Fernando Cladera Ojeda, Anthony Bisulco, Daniel R. Kepple, Volkan Isler, Daniel D. Lee:
On-Device Event Filtering with Binary Neural Networks for Pedestrian Detection Using Neuromorphic Vision Sensors. ICIP 2020: 3084-3088 - [c114]Eric Mitchell, Selim Engin, Volkan Isler, Daniel D. Lee:
Higher-Order Function Networks for Learning Composable 3D Object Representations. ICLR 2020 - [c113]Selim Engin, Eric Mitchell, Daewon Lee, Volkan Isler, Daniel D. Lee:
Higher Order Function Networks for View Planning and Multi-View Reconstruction. ICRA 2020: 11486-11492 - [c112]Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee:
Reward Prediction Error as an Exploration Objective in Deep RL. IJCAI 2020: 2816-2823 - [c111]Xiaoran Fan, Daewon Lee, Yuan Chen, Colin Prepscius, Volkan Isler, Larry D. Jackel, H. Sebastian Seung, Daniel D. Lee:
Acoustic Collision Detection and Localization for Robot Manipulators. IROS 2020: 9529-9536 - [c110]Jinwook Huh, Galen Xing, Ziyun Wang, Volkan Isler, Daniel D. Lee:
Learning to Generate Cost-to-Go Functions for Efficient Motion Planning. ISER 2020: 555-565 - [c109]Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel Dongyuel Lee:
Near-Chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection. ISVLSI 2020: 234-239 - [i35]Tarik Tosun, Daniel Yang, Ben Eisner, Volkan Isler, Daniel D. Lee:
Robotic Grasping through Combined image-Based Grasp Proposal and 3D Reconstruction. CoRR abs/2003.01649 (2020) - [i34]Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee:
Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection. CoRR abs/2004.01689 (2020) - [i33]Ziyun Wang, Eric A. Mitchell, Volkan Isler, Daniel D. Lee:
Geodesic-HOF: 3D Reconstruction Without Cutting Corners. CoRR abs/2006.07981 (2020) - [i32]Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Learning to Track Dynamic Targets in Partially Known Environments. CoRR abs/2006.10190 (2020) - [i31]Jinwook Huh, Galen Xing, Ziyun Wang, Volkan Isler, Daniel D. Lee:
Learning to Generate Cost-to-Go Functions for Efficient Motion Planning. CoRR abs/2010.14597 (2020) - [i30]Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee:
Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors. CoRR abs/2011.09427 (2020) - [i29]Niko A. Grupen, Daniel D. Lee, Bart Selman:
Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems. CoRR abs/2011.14890 (2020) - [i28]Jinwook Huh, Volkan Isler, Daniel D. Lee:
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning. CoRR abs/2012.06023 (2020)
2010 – 2019
- 2019
- [j21]Kanghoon Lee, Geon-hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim:
Bayesian optimistic Kullback-Leibler exploration. Mach. Learn. 108(5): 765-783 (2019) - [j20]Minoru Asada, Peter Stone, Manuela Veloso, Daniel D. Lee, Daniele Nardi:
RoboCup: A Treasure Trove of Rich Diversity for Research Issues and Interdisciplinary Connections [TC Spotlight]. IEEE Robotics Autom. Mag. 26(3): 99-102 (2019) - [j19]Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro:
Learning Optimal Resource Allocations in Wireless Systems. IEEE Trans. Signal Process. 67(10): 2775-2790 (2019) - [c108]Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro:
Dual Domain Learning of Optimal Resource Allocations in Wireless Systems. ICASSP 2019: 4729-4733 - [c107]Bhoram Lee, Clark Zhang, Zonghao Huang, Daniel D. Lee:
Online Continuous Mapping using Gaussian Process Implicit Surfaces. ICRA 2019: 6884-6890 - [c106]Heejin Jeong, Clark Zhang, George J. Pappas, Daniel D. Lee:
Assumed Density Filtering Q-learning. IJCAI 2019: 2607-2613 - [c105]Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Learning Q-network for Active Information Acquisition. IROS 2019: 6822-6827 - [c104]Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee:
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. IROS 2019: 7431-7438 - [c103]Jinwook Huh, Ömür Arslan, Daniel D. Lee:
Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. ISRR 2019: 311-327 - [i27]Jinwook Huh, Omur Arslan, Daniel D. Lee:
Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. CoRR abs/1901.00101 (2019) - [i26]Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee:
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies. CoRR abs/1903.10605 (2019) - [i25]Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee:
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. CoRR abs/1904.03260 (2019) - [i24]Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee:
QXplore: Q-learning Exploration by Maximizing Temporal Difference Error. CoRR abs/1906.08189 (2019) - [i23]Eric Mitchell, Kazim Selim Engin, Volkan Isler, Daniel D. Lee:
Higher-Order Function Networks for Learning Composable 3D Object Representations. CoRR abs/1907.10388 (2019) - [i22]Selim Engin, Eric Mitchell, Daewon Lee, Volkan Isler, Daniel D. Lee:
Higher Order Function Networks for View Planning and Multi-View Reconstruction. CoRR abs/1910.02066 (2019) - [i21]Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Learning Q-network for Active Information Acquisition. CoRR abs/1910.10754 (2019) - [i20]Ziyun Wang, Volkan Isler, Daniel D. Lee:
Surface HOF: Surface Reconstruction from a Single Image Using Higher Order Function Networks. CoRR abs/1912.08852 (2019) - 2018
- [j18]Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee:
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. 30(7) (2018) - [j17]SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee:
Learning Data Manifolds with a Cutting Plane Method. Neural Comput. 30(10) (2018) - [j16]Yung-Kyun Noh, Jihun Hamm, Frank Chongwoo Park, Byoung-Tak Zhang, Daniel D. Lee:
Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 40(1): 92-105 (2018) - [j15]Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee:
Generative Local Metric Learning for Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. 40(1): 106-118 (2018) - [j14]Jinwook Huh, Daniel D. Lee:
Efficient Sampling With Q-Learning to Guide Rapidly Exploring Random Trees. IEEE Robotics Autom. Lett. 3(4): 3868-3875 (2018) - [c102]Christopher W. Lynn, Daniel D. Lee:
Maximizing Activity in Ising Networks via the TAP Approximation. AAAI 2018: 679-686 - [c101]Heejin Jeong, Daniel D. Lee:
Bayesian Q-learning with Assumed Density Filtering. AAAI Spring Symposia 2018 - [c100]Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro:
Online Deep Learning in Wireless Communication Systems. ACSSC 2018: 1289-1293 - [c99]Steven W. Chen, Kelsey Saulnier, Nikolay Atanasov, Daniel D. Lee, Vijay Kumar, George J. Pappas, Manfred Morari:
Approximating Explicit Model Predictive Control Using Constrained Neural Networks. ACC 2018: 1520-1527 - [c98]Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee:
Memory Augmented Control Networks. ICLR (Poster) 2018 - [c97]Jinwook Huh, Bhoram Lee, Daniel D. Lee:
Constrained Sampling-Based Planning for Grasping and Manipulation. ICRA 2018: 223-230 - [c96]Xiang Deng, Daniel D. Lee:
Artificial Invariant Subspace for Humanoid Robot Balancing in Locomotion. IROS 2018: 185-192 - [c95]Clark Zhang, Jinwook Huh, Daniel D. Lee:
Learning Implicit Sampling Distributions for Motion Planning. IROS 2018: 3654-3661 - [c94]Marcell Missura, Daniel D. Lee, Maren Bennewitz:
Minimal Construct: Efficient Shortest Path Finding for Mobile Robots in Polygonal Maps. IROS 2018: 7918-7923 - [e4]Daniel D. Lee, Alexander Steen, Toby Walsh:
GCAI-2018, 4th Global Conference on Artificial Intelligence, Luxembourg, September 18-21, 2018. EPiC Series in Computing 55, EasyChair 2018 [contents] - [i19]Christopher W. Lynn, Daniel D. Lee:
Maximizing Activity in Ising Networks via the TAP Approximation. CoRR abs/1803.00110 (2018) - [i18]Christopher W. Lynn, Lia Papadopoulos, Daniel D. Lee, Danielle S. Bassett:
Surges of collective human activity emerge from simple pairwise correlations. CoRR abs/1803.00118 (2018) - [i17]Shouvik Ganguly, Jongha Ryu, Young-Han Kim, Yung-Kyun Noh, Daniel D. Lee:
Nearest neighbor density functional estimation based on inverse Laplace transform. CoRR abs/1805.08342 (2018) - [i16]Arbaaz Khan, Clark Zhang, Daniel D. Lee, Vijay Kumar, Alejandro Ribeiro:
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients. CoRR abs/1805.08776 (2018) - [i15]Clark Zhang, Jinwook Huh, Daniel D. Lee:
Learning Implicit Sampling Distributions for Motion Planning. CoRR abs/1806.01968 (2018) - [i14]Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro:
Learning Optimal Resource Allocations in Wireless Systems. CoRR abs/1807.08088 (2018) - [i13]Ty Nguyen, Tolga Özaslan, Ian D. Miller, James Keller, Giuseppe Loianno, Camillo J. Taylor, Daniel D. Lee, Vijay Kumar, Joseph H. Harwood, Jennifer M. Wozencraft:
U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification. CoRR abs/1809.06576 (2018) - 2017
- [j13]Stephen G. McGill, Seung-Joon Yi, Hak Yi, Min Sung Ahn, Sanghyun Cho, Kevin Liu, Daniel Sun, Bhoram Lee, Heejin Jeong, Jinwook Huh, Dennis W. Hong, Daniel D. Lee:
Team THOR's Entry in the DARPA Robotics Challenge Finals 2015. J. Field Robotics 34(4): 775-801 (2017) - [c93]Jinwook Huh, Bhoram Lee, Daniel D. Lee:
Adaptive motion planning with high-dimensional mixture models. ICRA 2017: 3740-3747 - [c92]Marcell Missura, Daniel D. Lee, Oskar von Stryk, Maren Bennewitz:
The synchronized holonomic model: A framework for efficient generation of motion. IROS 2017: 2076-2082 - [c91]Xiang Deng, Fei Miao, Daniel D. Lee:
Artificial invariant subspace with potential functions for humanoid robot balancing. IROS 2017: 4538-4545 - [c90]Bhoram Lee, Daniel D. Lee:
Self-supervised online learning of appearance for 3D tracking. IROS 2017: 4930-4937 - [c89]Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee:
Generative Local Metric Learning for Kernel Regression. NIPS 2017: 2452-2462 - [e3]Sven Behnke, Raymond Sheh, Sanem Sariel, Daniel D. Lee:
RoboCup 2016: Robot World Cup XX [Leipzig, Germany, June 30 - July 4, 2016]. Lecture Notes in Computer Science 9776, Springer 2017, ISBN 978-3-319-68791-9 [contents] - [i12]Steven W. Chen, Nikolay Atanasov, Arbaaz Khan, Konstantinos Karydis, Daniel D. Lee, Vijay Kumar:
Neural Network Memory Architectures for Autonomous Robot Navigation. CoRR abs/1705.08049 (2017) - [i11]SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee:
Learning Data Manifolds with a Cutting Plane Method. CoRR abs/1705.09944 (2017) - [i10]Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Daniel D. Lee, Vijay Kumar:
End-to-End Navigation in Unknown Environments using Neural Networks. CoRR abs/1707.07385 (2017) - [i9]Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee:
Memory Augmented Control Networks. CoRR abs/1709.05706 (2017) - [i8]SueYeon Chung, Daniel D. Lee, Haim Sompolinsky:
Classification and Geometry of General Perceptual Manifolds. CoRR abs/1710.06487 (2017) - [i7]Heejin Jeong, Daniel D. Lee:
Bayesian Q-learning with Assumed Density Filtering. CoRR abs/1712.03333 (2017) - 2016
- [j12]Seung-Joon Yi, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Whole-Body Balancing Walk Controller for Position Controlled Humanoid Robots. Int. J. Humanoid Robotics 13(1): 1650011:1-1650011:28 (2016) - [j11]Zhuo Wang, Alan A. Stocker, Daniel D. Lee:
Efficient Neural Codes That Minimize Lp Reconstruction Error. Neural Comput. 28(12): 2656-2686 (2016) - [c88]Heejin Jeong, Daniel D. Lee:
Learning Complex Stand-Up Motion for Humanoid Robots. AAAI 2016: 4218-4219 - [c87]Seung-Joon Yi, Daniel D. Lee:
Dynamic heel-strike toe-off walking controller for full-size modular humanoid robots. Humanoids 2016: 395-400 - [c86]Jinwook Huh, Daniel D. Lee:
Learning high-dimensional Mixture Models for fast collision detection in Rapidly-Exploring Random Trees. ICRA 2016: 63-69 - [c85]Stephen G. McGill, Seung-Joon Yi, Daniel D. Lee:
Low dimensional human preference tracking for motion optimization. ICRA 2016: 2867-2872 - [c84]Bhoram Lee, Daniel D. Lee:
Learning anisotropic ICP (LA-ICP) for robust and efficient 3D registration. ICRA 2016: 5040-5045 - [c83]Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee:
Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI 2016: 1571-1577 - [c82]Heejin Jeong, Daniel D. Lee:
Efficient learning of stand-up motion for humanoid robots with bilateral symmetry. IROS 2016: 1544-1549 - [c81]Bhoram Lee, Daniel D. Lee:
Online learning of visibility and appearance for object pose estimation. IROS 2016: 2792-2798 - [c80]Seung-Joon Yi, Daniel D. Lee:
Heel and toe lifting walk controller for resource constrained humanoid robots. IROS 2016: 5452-5458 - [c79]Christopher Lynn, Daniel D. Lee:
Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution. NIPS 2016: 2487-2495 - [c78]Zhuo Wang, Xue-Xin Wei, Alan A. Stocker, Daniel D. Lee:
Efficient Neural Codes under Metabolic Constraints. NIPS 2016: 4619-4627 - [c77]Yongbo Qian, Daniel D. Lee:
Adaptive Field Detection and Localization in Robot Soccer. RoboCup 2016: 218-229 - [p2]Jan Peters, Daniel D. Lee, Jens Kober, Duy Nguyen-Tuong, J. Andrew Bagnell, Stefan Schaal:
Robot Learning. Springer Handbook of Robotics, 2nd Ed. 2016: 357-398 - [e2]Daniel D. Lee, Masashi Sugiyama, Ulrike von Luxburg, Isabelle Guyon, Roman Garnett:
Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain. 2016 [contents] - [i6]Christopher Lynn, Daniel D. Lee:
Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution. CoRR abs/1608.06850 (2016) - 2015
- [j10]Yung-Kyun Noh, Daniel D. Lee, Kyung-Ae Yang, Cheong-Tag Kim, Byoung-Tak Zhang:
Molecular learning with DNA kernel machines. Biosyst. 137: 73-83 (2015) - [j9]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:
Team THOR's Entry in the DARPA Robotics Challenge Trials 2013. J. Field Robotics 32(3): 315-335 (2015) - [c76]Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee:
Reactive bandits with attitude. AISTATS 2015 - [c75]Pedro A. Ortega, Daniel D. Lee, Alan A. Stocker:
Causal reasoning in a prediction task with hidden causes. CogSci 2015 - [c74]Seung-Joon Yi, Dennis W. Hong, Daniel D. Lee:
Heel and toe lifting walk controller for traversing uneven terrain. Humanoids 2015: 325-330 - [c73]Stephen G. McGill, Seung-Joon Yi, Daniel D. Lee:
Team THOR's adaptive autonomy for disaster response humanoids. Humanoids 2015: 453-460 - [c72]Bhoram Lee, Kostas Daniilidis, Daniel D. Lee:
Online self-supervised monocular visual odometry for ground vehicles. ICRA 2015: 5232-5238 - [c71]Christopher Clingerman, Peter J. Wei, Daniel D. Lee:
Dynamic and probabilistic estimation of manipulable obstacles for indoor navigation. IROS 2015: 6121-6128 - [c70]Pedro A. Ortega, Koby Crammer, Daniel D. Lee:
Belief flows for robust online learning. ITA 2015: 70-77 - [c69]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 Humanoid AdultSize League Winner. RoboCup 2015: 132-143 - [e1]Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, Roman Garnett:
Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada. 2015 [contents] - [i5]Pedro A. Ortega, Koby Crammer, Daniel D. Lee:
Belief Flows of Robust Online Learning. CoRR abs/1505.07067 (2015) - [i4]Bob Carpenter, Matthew D. Hoffman, Marcus A. Brubaker, Daniel D. Lee, Peter Li, Michael Betancourt:
The Stan Math Library: Reverse-Mode Automatic Differentiation in C++. CoRR abs/1509.07164 (2015) - [i3]SueYeon Chung, Daniel D. Lee, Haim Sompolinsky:
Classification of Manifolds by Single-Layer Neural Networks. CoRR abs/1512.01834 (2015) - 2014
- [c68]Pedro A. Ortega, Daniel D. Lee:
An Adversarial Interpretation of Information-Theoretic Bounded Rationality. AAAI 2014: 2483-2489 - [c67]Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee:
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. AISTATS 2014: 669-677 - [c66]Christopher Clingerman, Daniel D. Lee:
Estimating manipulability of unknown obstacles for navigation in indoor environments. ICRA 2014: 2771-2778 - [c65]Seung-Joon Yi, Stephen G. McGill, Larry Vadakedathu, Qin He, Inyong Ha, Michael Rouleau, Dennis W. Hong, Daniel D. Lee:
Modular low-cost humanoid platform for disaster response. IROS 2014: 965-972 - [c64]Alexander Burka, Alaric Qin, Daniel D. Lee:
An application of parametric speaker technology to bus-pedestrian collision warning. ITSC 2014: 948-953 - [c63]Seung-Joon Yi, Steve McGill, Qin He, Larry Vadakedathu, Hak Yi, Sanghyun Cho, Dennis W. Hong, Daniel D. Lee:
RoboCup 2014 Humanoid AdultSize League Winner. RoboCup 2014: 94-105 - [c62]Seung-Joon Yi, Stephen G. McGill, Larry Vadakedathu, Qin He, Inyong Ha, Jeakweon Han, Hyunjong Song, Michael Rouleau, Dennis W. Hong, Daniel D. Lee:
THOR-OP humanoid robot for DARPA Robotics Challenge Trials 2013. URAI 2014: 359-363 - [i2]Pedro A. Ortega, Daniel D. Lee:
An Adversarial Interpretation of Information-Theoretic Bounded Rationality. CoRR abs/1404.5668 (2014) - 2013
- [c61]Yung-Kyun Noh, Frank Chongwoo Park, Daniel D. Lee:
k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling. CogSci 2013 - [c60]Seung-Joon Yi, Dennis W. Hong, Daniel D. Lee:
A hybrid walk controller for resource-constrained humanoid robots. Humanoids 2013: 88-93 - [c59]Seung-Joon Yi, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Online learning of low dimensional strategies for high-level push recovery in bipedal humanoid robots. ICRA 2013: 1649-1655 - [c58]Zhuo Wang, Alan A. Stocker, Daniel D. Lee:
Optimal Neural Population Codes for High-dimensional Stimulus Variables. NIPS 2013: 297-305 - [c57]Daniel D. Lee, Seung-Joon Yi, Stephen G. McGill, Yida Zhang, Larry Vadakedathu, Samarth Brahmbhatt, Richa Agrawal, Vibhavari Dasagi:
RoboCup 2013 Humanoid Kidsize League Winner. RoboCup 2013: 49-55 - [c56]Stephen G. McGill, Seung-Joon Yi, Yida Zhang, Daniel D. Lee:
Extensions of a RoboCup Soccer Software Framework. RoboCup 2013: 608-615 - 2012
- [j8]Shin'ichi Yuta, Daniel D. Lee, Keiji Nagatani, Yasushi Nakauchi:
Preface. Adv. Robotics 26(14): 1537-1538 (2012) - [j7]Keiji Nagatani, Alex Kushleyev, Daniel D. Lee:
Sensor Information Processing in Robot Competitions and Real World Robotic Challenges. Adv. Robotics 26(14): 1539-1554 (2012) - [j6]Paul Vernaza, Daniel D. Lee:
Learning and exploiting low-dimensional structure for efficient holonomic motion planning in high-dimensional spaces. Int. J. Robotics Res. 31(14): 1739-1760 (2012) - [j5]Jonathan Butzke, Kostas Daniilidis, Aleksandr Kushleyev, Daniel D. Lee, Maxim Likhachev, Cody J. Phillips, Mike Phillips:
The University of Pennsylvania MAGIC 2010 multi-robot unmanned vehicle system. J. Field Robotics 29(5): 745-761 (2012) - [c55]Seung-Joon Yi, Stephen G. McGill, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Active stabilization of a humanoid robot for real-time imitation of a human operator. Humanoids 2012: 761-766 - [c54]Koby Crammer, Daniel D. Lee:
Online discriminative learning of phoneme recognition via collections of generalized linear models. ICASSP 2012: 1961-1964 - [c53]Seung-Joon Yi, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Active stabilization of a humanoid robot for impact motions with unknown reaction forces. IROS 2012: 4034-4039 - [c52]Yung-Kyun Noh, Frank Chongwoo Park, Daniel D. Lee:
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification. NIPS 2012: 1934-1942 - [c51]Zhuo Wang, Alan A. Stocker, Daniel D. Lee:
"Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss". NIPS 2012: 2177-2185 - 2011
- [c50]Paul Vernaza, Daniel D. Lee:
Learning Dimensional Descent for Optimal Motion Planning in High-dimensional Spaces. AAAI 2011: 1126-1132 - [c49]Seung-Joon Yi, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Online learning of a full body push recovery controller for omnidirectional walking. Humanoids 2011: 1-6 - [c48]Stephen G. McGill, Daniel D. Lee:
Cooperative humanoid stretcher manipulation and locomotion. Humanoids 2011: 429-433 - [c47]Seung-Joon Yi, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Learning full body push recovery control for small humanoid robots. ICRA 2011: 2047-2052 - [c46]Paul Vernaza, Daniel D. Lee:
Efficient dynamic programming for high-dimensional, optimal motion planning by spectral learning of approximate value function symmetries. ICRA 2011: 6121-6127 - [c45]Paul Vernaza, Daniel D. Lee:
Learning Dimensional Descent planning for a highly-articulated robot arm. IROS 2011: 2186-2191 - [c44]Seung-Joon Yi, Byoung-Tak Zhang, Dennis W. Hong, Daniel D. Lee:
Practical bipedal walking control on uneven terrain using surface learning and push recovery. IROS 2011: 3963-3968 - [c43]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 Humanoid League Winners. RoboCup 2011: 37-50 - [i1]Yuan Shi, Yung-Kyun Noh, Fei Sha, Daniel D. Lee:
Learning Discriminative Metrics via Generative Models and Kernel Learning. CoRR abs/1109.3940 (2011) - 2010
- [c42]Seung-Joon Yi, Byoung-Tak Zhang, Daniel D. Lee:
Online Learning of Uneven Terrain for Humanoid Bipedal Walking. AAAI 2010: 1639-1644 - [c41]Paul Vernaza, Daniel D. Lee, Seung-Joon Yi:
Learning and planning high-dimensional physical trajectories via structured Lagrangians. ICRA 2010: 846-852 - [c40]Paul Vernaza, Daniel D. Lee:
Scalable real-time object recognition and segmentation via cascaded, discriminative Markov random fields. ICRA 2010: 3102-3107 - [c39]Koby Crammer, Daniel D. Lee:
Learning via Gaussian Herding. NIPS 2010: 451-459 - [c38]Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee:
Generative Local Metric Learning for Nearest Neighbor Classification. NIPS 2010: 1822-1830 - [c37]Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee:
Fluid Dynamics Models for Low Rank Discriminant Analysis. AISTATS 2010: 565-572
2000 – 2009
- 2009
- [c36]Jonathan Bohren, Tully Foote, Jim Keller, Alex Kushleyev, Daniel D. Lee, Alex Stewart, Paul Vernaza, Jason C. Derenick, John R. Spletzer, Brian Satterfield:
Little Ben: The Ben Franklin Racing Team's Entry in the 2007 DARPA Urban Challenge. The DARPA Urban Challenge 2009: 231-255 - [c35]Paul Vernaza, Maxim Likhachev, Subhrajit Bhattacharya, Sachin Chitta, Aleksandr Kushleyev, Daniel D. Lee:
Search-based planning for a legged robot over rough terrain. ICRA 2009: 2380-2387 - [c34]Yuanqing Lin, Shenghuo Zhu, Daniel D. Lee, Ben Taskar:
Learning Sparse Markov Network Structure via Ensemble-of-Trees Models. AISTATS 2009: 360-367 - 2008
- [j4]Jonathan Bohren, Tully Foote, Jim Keller, Alex Kushleyev, Daniel D. Lee, Alex Stewart, Paul Vernaza, Jason C. Derenick, John R. Spletzer, Brian Satterfield:
Little Ben: The Ben Franklin Racing Team's entry in the 2007 DARPA Urban Challenge. J. Field Robotics 25(9): 598-614 (2008) - [c33]Jihun Ham, Daniel D. Lee:
Grassmann discriminant analysis: a unifying view on subspace-based learning. ICML 2008: 376-383 - [c32]Yung-Kyun Noh, Jihun Ham, Daniel D. Lee:
Regularized discriminant analysis for transformation-invariant object recognition. ICPR 2008: 1-5 - [c31]Paul Vernaza, Ben Taskar, Daniel D. Lee:
Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields. ICRA 2008: 2750-2757 - [c30]Jihun Ham, Daniel D. Lee:
Extended Grassmann Kernels for Subspace-Based Learning. NIPS 2008: 601-608 - [c29]Jihun Ham, Daniel D. Lee:
Learning a Warped Subspace Model of Faces with Images of Unknown Pose and Illumination. VISAPP (1) 2008: 219-226 - 2007
- [j3]Fei Sha, Yuanqing Lin, Lawrence K. Saul, Daniel D. Lee:
Multiplicative Updates for Nonnegative Quadratic Programming. Neural Comput. 19(8): 2004-2031 (2007) - [c28]Sachin Chitta, Paul Vemaza, Roman Geykhman, Daniel D. Lee:
Proprioceptive localilzatilon for a quadrupedal robot on known terrain. ICRA 2007: 4582-4587 - [c27]Yuanqing Lin, Jingdong Chen, Youngmoo E. Kim, Daniel D. Lee:
Blind channel identification for speech dereverberation using l1-norm sparse learning. NIPS 2007: 921-928 - 2006
- [j2]Yuanqing Lin, Daniel D. Lee:
Bayesian regularization and nonnegative deconvolution for room impulse response estimation. IEEE Trans. Signal Process. 54(3): 839-847 (2006) - [c26]Jihun Ham, Ikkjin Ahn, Daniel D. Lee:
Learning a manifold-constrained map between image sets: applications to matching and pose estimation. CVPR (1) 2006: 817-824 - [c25]Yuanqing Lin, Daniel D. Lee:
Bayesian L1-Norm Sparse Learning. ICASSP (5) 2006: 605-608 - [c24]Koby Crammer, Daniel D. Lee:
Room Impulse Response Estimation using Sparse Online Prediction and Absolute Loss. ICASSP (3) 2006: 748-751 - [c23]Paul Vernaza, Daniel D. Lee:
Rao-Blackwellized Particle Filtering for 6-DOF Estimation of Attitude and Position via GPS and Inertial Sensors. ICRA 2006: 1571-1578 - [c22]Paul Vernaza, Daniel D. Lee:
Robust GPS/INS-Aided Localization and Mapping Via GPS Bias Estimation. ISER 2006: 101-110 - [p1]Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham, Daniel D. Lee:
Spectral Methods for Dimensionality Reduction. Semi-Supervised Learning 2006: 292-308 - 2005
- [c21]Jihun Ham, Daniel D. Lee, Lawrence K. Saul:
Semisupervised alignment of manifolds. AISTATS 2005: 120-127 - [c20]Yuanqing Lin, Daniel D. Lee:
Relevant deconvolution for acoustic source estimation. ICASSP (5) 2005: 529-532 - [c19]Jihun Ham, Yuanqing Lin, Daniel D. Lee:
Learning nonlinear appearance manifolds for robot localization. IROS 2005: 2971-2976 - [c18]Yuanqing Lin, Paul Vernaza, Jihun Ham, Daniel D. Lee:
Cooperative relative robot localization with audible acoustic sensing. IROS 2005: 3764-3769 - 2004
- [c17]Yuanqing Lin, Daniel D. Lee, Lawrence K. Saul:
Nonnegative deconvolution for time of arrival estimation. ICASSP (2) 2004: 377-380 - [c16]Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf:
A kernel view of the dimensionality reduction of manifolds. ICML 2004 - [c15]Yuanqing Lin, Daniel D. Lee:
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation. NIPS 2004: 809-816 - 2003
- [c14]Fei Sha, Lawrence K. Saul, Daniel D. Lee:
Multiplicative Updates for Large Margin Classifiers. COLT 2003: 188-202 - [c13]Lawrence K. Saul, Fei Sha, Daniel D. Lee:
Statistical signal processing with nonnegativity constraints. INTERSPEECH 2003: 1001-1004 - 2002
- [c12]Fei Sha, Lawrence K. Saul, Daniel D. Lee:
Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. NIPS 2002: 1041-1048 - [c11]Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell Jr., Yann LeCun:
Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. NIPS 2002: 1181-1188 - 2001
- [c10]Lawrence K. Saul, Daniel D. Lee:
Multiplicative Updates for Classification by Mixture Models. NIPS 2001: 897-904 - 2000
- [j1]H. Sebastian Seung, Daniel D. Lee, Ben Y. Reis, David W. Tank:
The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback. J. Comput. Neurosci. 9(2): 171-185 (2000) - [c9]Daniel D. Lee, H. Sebastian Seung:
Algorithms for Non-negative Matrix Factorization. NIPS 2000: 556-562 - [c8]Oren Shriki, Haim Sompolinsky, Daniel D. Lee:
An Information Maximization Approach to Overcomplete and Recurrent Representations. NIPS 2000: 612-618
1990 – 1999
- 1999
- [c7]Daniel D. Lee, H. Sebastian Seung:
Learning in Intelligent Embedded Systems. USENIX Workshop on Embedded Systems 1999 - [c6]Oliver B. Downs, David J. C. MacKay, Daniel D. Lee:
The Nonnegative Boltzmann Machine. NIPS 1999: 428-434 - [c5]Daniel D. Lee, Uri Rokni, Haim Sompolinsky:
Algorithms for Independent Components Analysis and Higher Order Statistics. NIPS 1999: 491-497 - 1998
- [c4]Daniel D. Lee, Haim Sompolinsky:
Learning a Continuous Hidden Variable Model for Binary Data. NIPS 1998: 515-521 - 1997
- [c3]Nicholas D. Socci, Daniel D. Lee, H. Sebastian Seung:
The Rectified Gaussian Distribution. NIPS 1997: 350-356 - [c2]Daniel D. Lee, H. Sebastian Seung:
A Neural Network Based Head Tracking System. NIPS 1997: 908-914 - 1996
- [c1]Daniel D. Lee, H. Sebastian Seung:
Unsupervised Learning by Convex and Conic Coding. NIPS 1996: 515-521
Coauthor Index
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