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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
- 2023
[i45]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)- [i44]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) - [i43]Chanwoo Chun, Daniel D. Lee:
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks. CoRR abs/2305.10550 (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]