Nontawat Charoenphakdee
12 papers · 2019–2025 · 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
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πΊοΈ Taxonomy Completionist (26) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π€
Dynamic Duo
(10)
π
Grand Slam
β‘
Prolific Year Β· Productive
β
The Questioner
π
Century Club Β· Bronze
π
Conference Pioneer
π
Trend Setter
ποΈ
Keyword Collector
(66)
Top co-authors
Research topics
Machine Learning
(11)
Optimization & Theory Β· Machine Learning
(7)
Learning Types Β· Machine Learning
(6)
Deep Learning
(5)
Core Methods
(5)
Artificial Intelligence
(2)
Natural Language Processing
(2)
Reinforcement Learning
(2)
Applications Β· Natural Language Processing
(2)
Core AI
(2)
Learning Types Β· Deep Learning
(2)
Methods
(2)
Optimization & Theory Β· Deep Learning
(2)
Application Areas
(1)
Applications Β· Reinforcement Learning
(1)
Keywords
classification calibration
(2)
symmetric loss
(2)
text classification
(2)
semi-supervised learning
(2)
multi-class classification
(2)
imitation learning
(2)
classification with rejection
(2)
confidence score
(2)
proper loss
(2)
model evaluation
(1)
gradient boosting
(1)
multiple instance learning
(1)
cross-lingual transfer
(1)
document classification
(1)
maximum likelihood
(1)
cost-sensitive classification
(1)
bayes error
(1)
importance weighting
(1)
source domain
(1)
probability estimation
(1)
Papers
Calm Composite Losses: Being Improper Yet Proper Composite
AISTATS 2025
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification
ICLR 2023
Classification with Rejection Based on Cost-sensitive Classification
ICML 2021
Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph
EMNLP 2021
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective
CVPR 2021
Robust Imitation Learning from Noisy Demonstrations
AISTATS 2021
Learning from Aggregate Observations
NeurIPS 2020
Imitation Learning from Imperfect Demonstration
ICML 2019
Learning Only from Relevant Keywords and Unlabeled Documents
EMNLP 2019
On Symmetric Losses for Learning from Corrupted Labels
ICML 2019
On the Calibration of Multiclass Classification with Rejection
NeurIPS 2019
Unsupervised Domain Adaptation Based on Source-Guided Discrepancy
AAAI 2019