Wittawat Jitkrittum

Orcid: 0000-0002-9400-9262

According to our database1, Wittawat Jitkrittum authored at least 42 papers between 2007 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

2023
It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models.
CoRR, 2023

Learning to reject meets OOD detection: Are all abstentions created equal?
CoRR, 2023

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval.
CoRR, 2023

When Does Confidence-Based Cascade Deferral Suffice?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Discussion of 'Multiscale Fisher's Independence Test for Multivariate Dependence'.
CoRR, 2022

ELM: Embedding and Logit Margins for Long-Tail Learning.
CoRR, 2022

Post-hoc estimators for learning to defer to an expert.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Sketch is Worth a Thousand Words: Image Retrieval with Text and Sketch.
Proceedings of the Computer Vision - ECCV 2022, 2022

A Witness Two-Sample Test.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
ABCDP: Approximate Bayesian Computation with Differential Privacy.
Entropy, 2021

HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation.
CoRR, 2021

An Optimal Witness Function for Two-Sample Testing.
CoRR, 2021

Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces.
Proceedings of the 38th International Conference on Machine Learning, 2021

Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Kernel Distributionally Robust Optimization.
CoRR, 2020

Kernel Conditional Moment Test via Maximum Moment Restriction.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Testing Goodness of Fit of Conditional Density Models with Kernels.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Learning Kernel Tests Without Data Splitting.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

More Powerful Selective Kernel Tests for Feature Selection.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
ABCDP: Approximate Bayesian Computation Meets Differential Privacy.
CoRR, 2019

A Kernel Stein Test for Comparing Latent Variable Models.
CoRR, 2019

Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces.
CoRR, 2019

Kernel Stein Tests for Multiple Model Comparison.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fisher Efficient Inference of Intractable Models.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Kernel Mean Matching for Content Addressability of GANs.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Model Inference with Stein Density Ratio Estimation.
CoRR, 2018

Informative Features for Model Comparison.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
A Linear-Time Kernel Goodness-of-Fit Test.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

An Adaptive Test of Independence with Analytic Kernel Embeddings.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Interpretable Distribution Features with Maximum Testing Power.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

K2-ABC: Approximate Bayesian Computation with Kernel Embeddings.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Passing Expectation Propagation Messages with Kernel Methods.
CoRR, 2015

Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM).
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso.
Neural Comput., 2014

2013
Feature Selection via l<sub>1</sub>-Penalized Squared-Loss Mutual Information.
IEICE Trans. Inf. Syst., 2013

Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Feature Selection via L1-Penalized Squared-Loss Mutual Information
CoRR, 2012

High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso
CoRR, 2012

2008
Implementing News Article Category Browsing Based on Text Categorization Technique.
Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and International Conference on Intelligent Agent Technology, 2008

2007
Managing Offline Educational Web Contents with Search Engine Tools.
Proceedings of the Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers, 2007


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