Thomas G. Dietterich
13 papers · 2004–2022 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (34) π Academic Marathon Β· Full π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π±
Topic Pioneer
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(84)
π
Trend Setter
π
Century Club Β· Bronze
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Renaissance Researcher
(7)
Top co-authors
Research topics
Machine Learning
(12)
Core Methods
(8)
Artificial Intelligence
(6)
Core AI
(5)
Optimization & Theory
(5)
Bayesian & Probabilistic
(3)
Learning Types
(3)
Knowledge & Reasoning
(2)
Natural Language Processing
(2)
Application Areas
(2)
Applications
(2)
Representation
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Keywords
markov decision process
(2)
rule learning
(2)
pac learning
(2)
probabilistic inference
(2)
systematic bia
(2)
bayesian inference
(1)
anomaly detection
(1)
probabilistic modeling
(1)
sequence labeling
(1)
domain adaptation
(1)
multinomial classification
(1)
object detection
(1)
weakly supervised learning
(1)
supervised learning
(1)
depth estimation
(1)
structured prediction
(1)
expectation maximization
(1)
confidence calibration
(1)
monocular depth estimation
(1)
statistical modeling
(1)
Papers
PAC Guarantees and Effective Algorithms for Detecting Novel Categories
JMLR 2022
Confidence Calibration for Domain Generalization Under Covariate Shift
ICCV 2021
K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management
AAAI 2021
Three-quarter Sibling Regression for Denoising Observational Data
IJCAI 2019
HC-Search for Structured Prediction in Computer Vision
CVPR 2015
PAC Optimal MDP Planning with Application to Invasive Species Management
JMLR 2015
Active Imitation Learning: Formal and Practical Reductions to I.I.D. Learning
JMLR 2014
A Conditional Multinomial Mixture Model for Superset Label Learning
NeurIPS 2012
Collective Graphical Models
NeurIPS 2011
Inverting Grice's Maxims to Learn Rules from Natural Language Extractions
NeurIPS 2011
Learning Rules from Incomplete Examples via Implicit Mention Models
ACML 2011
Gradient Tree Boosting for Training Conditional Random Fields
JMLR 2008
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
JMLR 2004