Lee, Daniel D.

46 publications

NeurIPS 2022 A Theory of Weight Distribution-Constrained Learning Weishun Zhong, Ben Sorscher, Daniel D. Lee, Haim Sompolinsky

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

NeurIPS 2022 Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications Daniel D. Lee, Georgy Noarov, Mallesh Pai, Aaron Roth

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

NeurIPS 2021 Local Disentanglement in Variational Auto-Encoders Using Jacobian $l_1$ Regularization Travers Rhodes, Daniel D. Lee

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

ECCV 2020 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

IJCAI 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 2019 Assumed Density Filtering Q-Learning Heejin Jeong, Clark Zhang, George J. Pappas, Daniel D. Lee

MLJ 2019 Bayesian Optimistic Kullback-Leibler Exploration Kanghoon Lee, Geon-hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim

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

ICLR 2018 Memory Augmented Control Networks Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee

NeurIPS 2017 Generative Local Metric Learning for Kernel Regression Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank Park, Daniel D Lee

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

NeurIPS 2016 Efficient Neural Codes Under Metabolic Constraints Zhuo Wang, Xue-Xin Wei, Alan Stocker, Daniel D Lee

AAAI 2016 Learning Complex Stand-up Motion for Humanoid Robots Heejin Jeong, Daniel D. Lee

NeurIPS 2016 Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution Christopher Lynn, Daniel D Lee

AISTATS 2015 Reactive Bandits with Attitude Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee

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

AISTATS 2014 Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee

NeurIPS 2013 Optimal Neural Population Codes for High-Dimensional Stimulus Variables Zhuo Wang, Alan Stocker, Daniel D Lee

NeurIPS 2012 Diffusion Decision Making for Adaptive K-Nearest Neighbor Classification Yung-kyun Noh, Frank Park, Daniel D. Lee

NeurIPS 2012 Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss Zhuo Wang, Alan Stocker, Daniel D Lee

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

NeurIPS 2010 Generative Local Metric Learning for Nearest Neighbor Classification Yung-kyun Noh, Byoung-tak Zhang, Daniel D. Lee

NeurIPS 2010 Learning via Gaussian Herding Koby Crammer, Daniel D. Lee

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

NeurIPS 2008 Extended Grassmann Kernels for Subspace-Based Learning Jihun Hamm, Daniel D. Lee

ICML 2008 Grassmann Discriminant Analysis: A Unifying View on Subspace-Based Learning Jihun Ham, Daniel D. Lee

NeurIPS 2007 Blind Channel Identification for Speech Dereverberation Using L1-Norm Sparse Learning Yuanqing Lin, Jingdong Chen, Youngmoo Kim, Daniel D. Lee

CVPR 2006 Learning a Manifold-Constrained mAP Between Image Sets: Applications to Matching and Pose Estimation Jihun Ham, Ikkjin Ahn, Daniel D. Lee

NeurIPS 2005 Beyond Gaussian Processes: On the Distributions of Infinite Networks Ricky Der, Daniel D. Lee

ICML 2004 A Kernel View of the Dimensionality Reduction of Manifolds Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf

NeurIPS 2004 Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation Yuanqing Lin, Daniel D. Lee

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

NeurIPS 2002 Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines Fei Sha, Lawrence K. Saul, Daniel D. Lee

NeurIPS 2002 Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell, Yann L. Cun

NeurIPS 2001 Multiplicative Updates for Classification by Mixture Models Lawrence K. Saul, Daniel D. Lee

NeurIPS 2000 Algorithms for Non-Negative Matrix Factorization Daniel D. Lee, H. Sebastian Seung

NeurIPS 2000 An Information Maximization Approach to Overcomplete and Recurrent Representations Oren Shriki, Haim Sompolinsky, Daniel D. Lee

NeurIPS 1999 Algorithms for Independent Components Analysis and Higher Order Statistics Daniel D. Lee, Uri Rokni, Haim Sompolinsky

NeurIPS 1999 The Nonnegative Boltzmann Machine Oliver B. Downs, David J. C. MacKay, Daniel D. Lee

NeurIPS 1998 Learning a Continuous Hidden Variable Model for Binary Data Daniel D. Lee, Haim Sompolinsky

NeurIPS 1997 A Neural Network Based Head Tracking System Daniel D Lee, H. S. Seung

NeurIPS 1997 The Rectified Gaussian Distribution Nicholas D. Socci, Daniel D. Lee, H. Sebastian Seung

NeurIPS 1996 Unsupervised Learning by Convex and Conic Coding Daniel D. Lee, H. Sebastian Seung