← Authors

Daniel D. Lee

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

Achievements

🌍 Conference Polyglot (6) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (7) πŸ—ΊοΈ Taxonomy Completionist (17) 🧭 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