Daniel D. Lee
19 papers · 2007–2022 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (57) π Academic Marathon Β· Full π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Champion
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(4)
π
Trend Setter
π₯
Unstoppable Β· Bronze
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Conference Pioneer
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Renaissance Researcher
(7)
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Century Club Β· Bronze
ποΈ
Keyword Collector
(122)
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory
(11)
Core Methods
(10)
Learning Types Β· Machine Learning
(6)
Mathematics & Optimization
(5)
Interdisciplinary
(4)
Cognitive Science
(4)
Optimization
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Learning Types Β· Deep Learning
(3)
Reinforcement Learning
(2)
Bayesian & Probabilistic
(2)
Core AI
(2)
Mathematics
(2)
Keywords
metric learning
(3)
dimensionality reduction
(3)
information theory
(2)
tuning curve
(2)
kullback-leibler divergence
(2)
nearest neighbor
(2)
optimal coding
(2)
mutual information
(2)
generative model
(2)
gaussian distribution
(2)
stimulus distribution
(2)
nearest neighbor classification
(2)
online learning
(2)
neural coding
(2)
sparse learning
(1)
independent component analysis
(1)
path planning
(1)
reinforcement learning
(1)
policy optimization
(1)
population coding
(1)
Papers
A theory of weight distribution-constrained learning
NeurIPS 2022
Cooperative Multi-Agent Fairness and Equivariant Policies
AAAI 2022
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications
NeurIPS 2022
Geodesic-HOF: 3D Reconstruction Without Cutting Corners
AAAI 2021
Local Disentanglement in Variational Auto-Encoders Using Jacobian L_1 Regularization
NeurIPS 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
NeurIPS 2017
Efficient Neural Codes under Metabolic Constraints
NeurIPS 2016
Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution
NeurIPS 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
NeurIPS 2013
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification
NeurIPS 2012
Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss
NeurIPS 2012
Generative Local Metric Learning for Nearest Neighbor Classification
NeurIPS 2010
Learning via Gaussian Herding
NeurIPS 2010
Extended Grassmann Kernels for Subspace-Based Learning
NeurIPS 2008
Blind channel identification for speech dereverberation using l1-norm sparse learning
NeurIPS 2007