← Authors

Wittawat Jitkrittum

27 papers · 2013–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (12) πŸ—ΊοΈ Taxonomy Completionist (11) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (5) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🐣 Hot Topic Early Bird πŸ† Keyword Champion (6) 🀝 Dynamic Duo (10) πŸ—ƒοΈ Keyword Collector (85) ❓ The Questioner ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (27) πŸ”₯ Unstoppable (11) πŸ“ˆ Trend Setter

Conferences

NIPS (9) ICML (6) ICLR (5) AISTATS (4) UAI (2) ECCV (1)

Top co-authors

Sanjiv Kumar (10) Bernhard SchΓΆlkopf (7) Harikrishna Narasimhan (7) Aditya Krishna Menon (6) Zoltan Szabo (4) Neha Gupta (4) Ankit Singh Rawat (4) Arthur Gretton (4) Patsorn Sangkloy (3) Aditya K Menon (3)

Research topics

Statistics (2)

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