Dean P. Foster
18 papers · 2006–2023 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (47) π Academic Marathon Β· Full π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Trendsetter Combo
(7)
π§
Keyword Pioneer
π
Century Club Β· Bronze
π
Conference Pioneer
π
Trend Setter
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(104)
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Renaissance Researcher
(6)
Top co-authors
Research topics
Machine Learning
(16)
Optimization & Theory Β· Machine Learning
(13)
Core Methods
(12)
Learning Types
(7)
Mathematics & Optimization
(6)
Mathematics
(4)
Optimization
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Natural Language Processing
(2)
Application Areas
(2)
Applications
(2)
Learning Paradigms
(2)
Optimization & Theory Β· Deep Learning
(2)
Computer Science
(1)
Keywords
ridge regression
(3)
singular value decomposition
(3)
online learning
(3)
sample complexity
(2)
dimensionality reduction
(2)
multi-view learning
(2)
randomized algorithm
(2)
high-dimensional regression
(2)
regret bound
(2)
canonical correlation analysis
(2)
spectral method
(2)
least square
(2)
reinforcement learning
(2)
randomized hadamard transform
(2)
high-dimensional data
(2)
convex optimization
(1)
policy optimization
(1)
imitation learning
(1)
non-convex optimization
(1)
learning theory
(1)
Papers
Linear Reinforcement Learning with Ball Structure Action Space
ALT 2023
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation
NeurIPS 2022
The Benefits of Implicit Regularization from SGD in Least Squares Problems
NeurIPS 2021
Dynamic Local Regret for Non-convex Online Forecasting
NeurIPS 2019
Eigenwords: Spectral Word Embeddings
JMLR 2015
large scale canonical correlation analysis with iterative least squares
NeurIPS 2014
Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity
JMLR 2014
A Risk Comparison of Ordinary Least Squares vs Ridge Regression
JMLR 2013
Experiments with Spectral Learning of Latent-Variable PCFGs
NAACL 2013
Faster Ridge Regression via the Subsampled Randomized Hadamard Transform
NeurIPS 2013
New Subsampling Algorithms for Fast Least Squares Regression
NeurIPS 2013
One-shot learning and big data with n=2
NeurIPS 2013
A Spectral Algorithm for Latent Dirichlet Allocation
NeurIPS 2012
Spectral Learning of Latent-Variable PCFGs
ACL 2012
Complexity-Based Approach to Calibration with Checking Rules
COLT 2011
Multi-View Learning of Word Embeddings via CCA
NeurIPS 2011
Stochastic convex optimization with bandit feedback
NeurIPS 2011
Streamwise Feature Selection
JMLR 2006