Wittawat Jitkrittum
27 papers · 2013–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (11) π Interdisciplinary Bridge π Conference Polyglot (6)
π
Interdisciplinary Bridge
π
Conference Polyglot
(6)
π£
Hot Topic Early Bird
π
Keyword Champion
(6)
π€
Dynamic Duo
(10)
ποΈ
Keyword Collector
(85)
β
The Questioner
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Century Club
(27)
π₯
Unstoppable
(11)
π
Trend Setter
Conferences
NIPS (9)
ICML (6)
ICLR (5)
AISTATS (4)
UAI (2)
ECCV (1)
Top co-authors
Research topics
Keywords
kernel methods
(8)
maximum mean discrepancy
(7)
statistical test
(6)
reproducing kernel hilbert space
(4)
hypothesis testing
(3)
two-sample test
(2)
stein operator
(2)
kernel embedding
(2)
goodness-of-fit test
(2)
goodness of fit
(2)
statistical testing
(2)
model comparison
(2)
cascade classifier
(1)
false discovery rate
(1)
feature selection
(1)
bayesian inference
(1)
image generation
(1)
representation learning
(1)
convex optimization
(1)
locally linear embedding
(1)
Papers
Faster Cascades via Speculative Decoding
ICLR 2025
Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
ICML 2025
Learning to Reject Meets Long-tail Learning
ICLR 2024
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval
ICML 2024
Language Model Cascades: Token-Level Uncertainty And Beyond
ICLR 2024
On Bias-Variance Alignment in Deep Models
ICLR 2024
Plugin estimators for selective classification with out-of-distribution detection
ICLR 2024
When Does Confidence-Based Cascade Deferral Suffice?
NIPS 2023
A Witness Two-Sample Test
AISTATS 2022
Post-hoc estimators for learning to defer to an expert
NIPS 2022
A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch
ECCV 2022
Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
AISTATS 2021
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
ICML 2021
Testing Goodness of Fit of Conditional Density Models with Kernels
UAI 2020
Learning Kernel Tests Without Data Splitting
NIPS 2020
More Powerful Selective Kernel Tests for Feature Selection
AISTATS 2020
Kernel Conditional Moment Test via Maximum Moment Restriction
UAI 2020
Kernel Mean Matching for Content Addressability of GANs
ICML 2019
Kernel Stein Tests for Multiple Model Comparison
NIPS 2019
Fisher Efficient Inference of Intractable Models
NIPS 2019
Informative Features for Model Comparison
NIPS 2018
An Adaptive Test of Independence with Analytic Kernel Embeddings
ICML 2017
A Linear-Time Kernel Goodness-of-Fit Test
NIPS 2017
Interpretable Distribution Features with Maximum Testing Power
NIPS 2016
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
AISTATS 2016
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
NIPS 2015
Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning
ICML 2013