Daniel D. Lee
19 papers · 2007–2022 · 6 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+11 more ↓ Show less ↑
π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (6) πΊοΈ Taxonomy Completionist (17) π£ Hot Topic Early Bird
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Academic Marathon
(15)
π
Keyword Trendsetter Combo
(4)
π±
Topic Pioneer
π
Keyword Champion
π
Trend Setter
π
Century Club
(19)
π
Conference Pioneer
ποΈ
Keyword Collector
(110)
π₯
Unstoppable
(7)
Conferences
NIPS (13)
AAAI (2)
AISTATS (1)
ECCV (1)
ICLR (1)
IJCAI (1)
Top co-authors
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