Jonathan Chang
12 papers · 2005–2022 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (29) 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₯
Mega-Team Β· Squad
π
Keyword Trendsetter Combo
(3)
π
Renaissance Researcher
(5)
π
Conference Pioneer
ποΈ
Keyword Collector
(65)
π
Trend Setter
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(8)
Core Methods
(6)
Learning Types
(4)
Artificial Intelligence
(3)
Natural Language Processing
(3)
Reinforcement Learning
(3)
Applications
(3)
Methods
(3)
Data Science & Analytics
(2)
Bayesian & Probabilistic
(2)
Core AI
(2)
Optimization & Theory
(2)
Resources & Methods
(2)
Deep Learning
(1)
Knowledge & Reasoning
(1)
Keywords
label propagation
(2)
unsupervised learning
(2)
topic model
(2)
imitation learning
(2)
multi-label classification
(2)
semi-supervised learning
(2)
social network
(2)
probabilistic modeling
(1)
offline reinforcement learning
(1)
stochastic gradient descent
(1)
text classification
(1)
probabilistic inference
(1)
interpretability
(1)
model-based learning
(1)
document clustering
(1)
sentiment analysis
(1)
behavior cloning
(1)
policy learning
(1)
topic modeling
(1)
binary classification
(1)
Papers
Learning Bellman Complete Representations for Offline Policy Evaluation
ICML 2022
Multitask Prompted Training Enables Zero-Shot Task Generalization
ICLR 2022
Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage
NeurIPS 2021
MobILE: Model-Based Imitation Learning From Observation Alone
NeurIPS 2021
Conversations Gone Awry: Detecting Early Signs of Conversational Failure
ACL 2018
Joint Label Inference in Networks
JMLR 2017
Joint Inference of Multiple Label Types in Large Networks
ICML 2014
Learning a Concept Hierarchy from Multi-labeled Documents
NeurIPS 2014
Erratum: SGDQN is Less Careful than Expected
JMLR 2010
Reading Tea Leaves: How Humans Interpret Topic Models
NeurIPS 2009
PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks
SemEval 2007
Relational Topic Models for Document Networks
AISTATS 2005