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← Authors

Daniel D. Lee

19 papers · 2007–2022 · 6 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (17) 🐣 Hot Topic Early Bird
🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (15) 🌟 Keyword Trendsetter Combo (4) 🌱 Topic Pioneer πŸ† Keyword Champion πŸ“ˆ Trend Setter πŸ’Ž Century Club (19) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (110) πŸ”₯ Unstoppable (7)

Conferences

NIPS (13) AAAI (2) AISTATS (1) ECCV (1) ICLR (1) IJCAI (1)

Top co-authors

Daniel D Lee (5) Yung-kyun Noh (4) Zhuo Wang (3) Alan Stocker (3) Frank Park (2) Volkan Isler (2) Clark Zhang (2) Masashi Sugiyama (2) Kee-eung Kim (1) Byoung-tak Zhang (1)

Keywords

dimensionality reduction (3) metric learning (3) neural coding (2) online learning (2) nearest neighbor (2) nearest neighbor classification (2) generative model (2) stimulus distribution (2) tuning curve (2) optimal coding (2) mutual information (2) density estimation (1) sparse learning (1) bayesian reinforcement learning (1) adversarial learning (1) independent component analysis (1) minimax optimization (1) policy optimization (1) 3d reconstruction (1) point cloud (1)

Papers

A theory of weight distribution-constrained learning NIPS 2022 Cooperative Multi-Agent Fairness and Equivariant Policies AAAI 2022 Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications NIPS 2022 Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization NIPS 2021 Geodesic-HOF: 3D Reconstruction Without Cutting Corners AAAI 2021 Jointly learning visual motion and confidence from local patches in event cameras ECCV 2020 Assumed Density Filtering Q-learning IJCAI 2019 Memory Augmented Control Networks ICLR 2018 Generative Local Metric Learning for Kernel Regression NIPS 2017 Efficient Neural Codes under Metabolic Constraints NIPS 2016 Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution NIPS 2016 Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence AISTATS 2014 Optimal Neural Population Codes for High-dimensional Stimulus Variables NIPS 2013 Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification NIPS 2012 Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss NIPS 2012 Learning via Gaussian Herding NIPS 2010 Generative Local Metric Learning for Nearest Neighbor Classification NIPS 2010 Extended Grassmann Kernels for Subspace-Based Learning NIPS 2008 Blind channel identification for speech dereverberation using l1-norm sparse learning NIPS 2007