Faculty

Institution

Unit

Venue

Daniel Dongyuel Lee

Professor

Cornell University

Affiliations

Cornell Tech

College of Engineering

School of Electrical and Computer Engineering

Daniel Dongyuel Lee is currently serving as a Cornell Tech Professor at Cornell University.

Honors

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Experiences

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Education

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Daniel Dongyuel Lee

Cornell University

Professor

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computer science machine learning robotics data science machine learning research robot learning applied mathematics image representation autonomous robots machine vision neural network (machine learning) artificial intelligence robotics automation computer vision computational intelligence mathematical optimization field robotics kinesiology pattern recognition kinematics humanoid robots neural computation trajectory planning path planning intelligent robot computational statistics intelligent robotic systems manifold learning geometric learning statistical learning theory robot kinematics computational optimization legged robots intelligent robotics robot control deep reinforcement learning supervised learning bipedal locomotion human robot interaction dimensionality reduction 3d computer vision manifold modeling nonlinear dimensionality reduction feature learning object detection neural network visual science speech processing autonomous navigation robotics perception learning control robotic sensing 3d vision moving object tracking neuronal networks object recognition multiplicative updates motion planning matrix factorization neurodynamics recurrent neural networks convex optimization vehicle localization learning algorithm team thor non-negative matrix factorization image manifolds optimal resource allocations object manifolds neural codes efficient neural codes uneven terrain pedestrian detection metric learning influence maximization active stabilization computational biology biological computation systems biology biosystems theoretical biology

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Estimating the Spectral Moments of the Kernel Integral Operator From Finite Sample Matrices. arXiv (Cornell University) (2024)

Chun, ChanwooChung, SueYeonLee, Daniel D.

statistical learning theoryreproducing kernel methodsspectral analysisapplied mathematicscomputational statisticseigenvalue spectrummachine learningdata sciencespectral momentskernel methodskernel integral operatorsignal processingspectral theoryneural network (machine learning)

Policy-Value Alignment and Robustness in Search-Based Multi-Agent Learning. arXiv (Cornell University) (2023)

Grupen, Niko A.Hanlon, MichaelHao, AlexisLee, Daniel D.Selman, Bart

multiagent systemscomputational intelligenceevolutionary intelligenceexploration v exploitationreinforcement learningcomputer sciencemachine learningintelligent systemsmulti-agent learningpolicy-value alignmentvalue generalization errorartificial intelligencerobot learningvalue robustness

Sparsity-Depth Tradeoff in Infinitely Wide Deep Neural Networks. arXiv (Cornell University) (2023)

Chun, ChanwooLee, Daniel D.

sparse representationscomputational intelligencesparse neural networkmachine learning researchgeneralization performancesparsity-depth tradeoffcomputer sciencemachine learningdata sciencekernel-ridge regressionneural computationgaussian processdeep learningneural network (machine learning)

TIMEWARPVAE: Simultaneous Time-Warping and Representation Learning of Trajectories. arXiv (Cornell University) (2023)

Rhodes, TraversLee, Daniel D.

meaningful novel trajectoriesmotion synthesismachine learning researchtimewarpvae algorithmgeometric learningcomputer sciencemachine learningdata sciencemanifold learningrepresentation learningrobot learningdeep learning

A Theory of Learning With Constrained Weight-Distribution. arXiv (Cornell University) (2022)

Zhong, WeishunSorscher, BenLee, Daniel DSompolinsky, Haim

mathematical optimizationstatistical learning theorycomputational intelligenceapplied mathematicsmachine learning researchoptimal transportneuronal networksstatistical mechanical theorygeometric learningsupervised learningmachine learningneuroscienceoptimal transport theorycomputational neuroscienceneural computationneural network (machine learning)

Cooperative Multi-Agent Fairness and Equivariant Policies. Proceedings of the AAAI Conference on Artificial Intelligence (2022)

Niko A. GrupenBart SelmanDaniel D. Lee

multiagent systemscooperationreinforcement learningsocial choicemulti-agent learningcooperative multi-agent learningfairnessgroup decisionalgorithmic fairnesscooperative multi-agent fairness

Learning From Demonstration Using a Curvature Regularized Variational Auto-Encoder (Curvvae). 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022)

Travers RhodesTapomayukh BhattacharjeeDaniel D. Lee

robotics automationintricate manipulation skillsreinforcement learningroboticsgeometric learningmachine learninghuman robot interactionartificial intelligencephysical robot systemrobot learningslippery banana slicesdeep learningobject manipulation

Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. IEEE Transactions on Information Theory (2022)

J. Jon RyuShouvik GangulyYoung-Han KimYung-Kyun NohDaniel D. Lee

approximation theoryparameter estimationnumerical analysisconvergence rateapplied mathematicsinverse laplace transformstatistical methodologycomputational statisticsnumerical algorithmsdensity estimationinline-formula xmlnsstatistical inferencemathematicsapproximation methodsestimation theoryinverse problems

Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. Springer proceedings in advanced robotics (2022)

Jinwook HuhÖmür ArslanDaniel D. Lee

autonomous robotstrajectory planningsystems engineeringsafe corridorsroboticscomputer sciencepath planning

Simultaneous Object Reconstruction and Grasp Prediction Using a Camera-Centric Object Shell Representation. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022)

Nikhil Chavan-DafleSergiy PopovychShubham AgrawalDaniel D. LeeVolkan Isler

3d vision3d computer visionrobotics automationimage representationroboticsdexterous manipulationobject shellcomputer visionsimultaneous object reconstructionmachine visiondepth maprobot learningobject reconstructiondeep learningobject manipulation

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Daniel Dongyuel Lee

Professor

Cornell University

Affiliations

Cornell Tech

College of Engineering

School of Electrical and Computer Engineering

Daniel Dongyuel Lee is currently serving as a Cornell Tech Professor at Cornell University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Daniel Dongyuel Lee

Cornell University

Professor

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Estimating the Spectral Moments of the Kernel Integral Operator From Finite Sample Matrices. arXiv (Cornell University) (2024)

Chun, ChanwooChung, SueYeonLee, Daniel D.

Policy-Value Alignment and Robustness in Search-Based Multi-Agent Learning. arXiv (Cornell University) (2023)

Grupen, Niko A.Hanlon, MichaelHao, AlexisLee, Daniel D.Selman, Bart

Sparsity-Depth Tradeoff in Infinitely Wide Deep Neural Networks. arXiv (Cornell University) (2023)

Chun, ChanwooLee, Daniel D.

TIMEWARPVAE: Simultaneous Time-Warping and Representation Learning of Trajectories. arXiv (Cornell University) (2023)

Rhodes, TraversLee, Daniel D.

A Theory of Learning With Constrained Weight-Distribution. arXiv (Cornell University) (2022)

Zhong, WeishunSorscher, BenLee, Daniel DSompolinsky, Haim

Cooperative Multi-Agent Fairness and Equivariant Policies. Proceedings of the AAAI Conference on Artificial Intelligence (2022)

Niko A. GrupenBart SelmanDaniel D. Lee

multiagent systemscooperationreinforcement learningsocial choicemulti-agent learningcooperative multi-agent learningfairnessgroup decisionalgorithmic fairnesscooperative multi-agent fairness

Learning From Demonstration Using a Curvature Regularized Variational Auto-Encoder (Curvvae). 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022)

Travers RhodesTapomayukh BhattacharjeeDaniel D. Lee

Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. IEEE Transactions on Information Theory (2022)

J. Jon RyuShouvik GangulyYoung-Han KimYung-Kyun NohDaniel D. Lee

Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. Springer proceedings in advanced robotics (2022)

Jinwook HuhÖmür ArslanDaniel D. Lee

autonomous robotstrajectory planningsystems engineeringsafe corridorsroboticscomputer sciencepath planning

Simultaneous Object Reconstruction and Grasp Prediction Using a Camera-Centric Object Shell Representation. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022)

Nikhil Chavan-DafleSergiy PopovychShubham AgrawalDaniel D. LeeVolkan Isler

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