Wittawat Jitkrittum

According to our database, Wittawat Jitkrittum authored at least 50 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs.

Ankit Singh Rawat, Veeranjaneyulu Sadhanala, Afshin Rostamizadeh, Ayan Chakrabarti, Wittawat Jitkrittum, Vladimir Feinberg, Seungyeon Kim, Hrayr Harutyunyan, Nikunj Saunshi, Zachary Nado, Rakesh Shivanna, Sashank J. Reddi, Aditya Krishna Menon, Rohan Anil, Sanjiv Kumar

CoRR, 2024

Cascade-Aware Training of Language Models.

Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go

CoRR, 2024

Faster Cascades via Speculative Decoding.

Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar

CoRR, 2024

USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval.

Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Plugin estimators for selective classification with out-of-distribution detection.

Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning to Reject Meets Long-tail Learning.

Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Language Model Cascades: Token-Level Uncertainty And Beyond.

Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Bias-Variance Alignment in Deep Models.

Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

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

Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar

CoRR, 2023

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

Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar

CoRR, 2023

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval.

Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar

CoRR, 2023

When Does Confidence-Based Cascade Deferral Suffice?

Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar

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'.

Antonin Schrab, Wittawat Jitkrittum, Zoltán Szabó, Dino Sejdinovic, Arthur Gretton

CoRR, 2022

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

Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar

CoRR, 2022

Post-hoc estimators for learning to defer to an expert.

Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar

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.

Patsorn Sangkloy, Wittawat Jitkrittum, Diyi Yang, James Hays

Proceedings of the Computer Vision - ECCV 2022, 2022

A Witness Two-Sample Test.

Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

ABCDP: Approximate Bayesian Computation with Differential Privacy.

Mijung Park, Margarita Vinaroz, Wittawat Jitkrittum

Entropy, 2021

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

Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang

CoRR, 2021

An Optimal Witness Function for Two-Sample Testing.

Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

CoRR, 2021

Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces.

Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

Proceedings of the 38th International Conference on Machine Learning, 2021

Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation.

Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Kernel Distributionally Robust Optimization.

Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf

CoRR, 2020

Kernel Conditional Moment Test via Maximum Moment Restriction.

Krikamol Muandet, Wittawat Jitkrittum, Jonas M. Kübler

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Testing Goodness of Fit of Conditional Density Models with Kernels.

Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Learning Kernel Tests Without Data Splitting.

Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

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.

Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

More Powerful Selective Kernel Tests for Feature Selection.

Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

ABCDP: Approximate Bayesian Computation Meets Differential Privacy.

Mijung Park, Wittawat Jitkrittum

CoRR, 2019

A Kernel Stein Test for Comparing Latent Variable Models.

Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton

CoRR, 2019

Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces.

Arash Mehrjou, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

CoRR, 2019

Kernel Stein Tests for Multiple Model Comparison.

Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum

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.

Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen

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.

Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Model Inference with Stein Density Ratio Estimation.

Song Liu, Wittawat Jitkrittum, Carl Henrik Ek

CoRR, 2018

Informative Features for Model Comparison.

Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton

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.

Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton

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.

Wittawat Jitkrittum, Zoltán Szabó, Arthur Gretton

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Interpretable Distribution Features with Maximum Testing Power.

Wittawat Jitkrittum, Zoltán Szabó, Kacper P. Chwialkowski, Arthur Gretton

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.

Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Passing Expectation Propagation Messages with Kernel Methods.

Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess

CoRR, 2015

Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.

Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM).

Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó, Lars Buesing, Maneesh Sahani

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.

Makoto Yamada, Wittawat Jitkrittum, Leonid Sigal, Eric P. Xing, Masashi Sugiyama

Neural Comput., 2014

2013

Feature Selection via l₁-Penalized Squared-Loss Mutual Information.

Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama

IEICE Trans. Inf. Syst., 2013

Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning.

Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Feature Selection via L1-Penalized Squared-Loss Mutual Information

Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama

CoRR, 2012

High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso

Makoto Yamada, Wittawat Jitkrittum, Leonid Sigal, Masashi Sugiyama

CoRR, 2012

2008

Implementing News Article Category Browsing Based on Text Categorization Technique.

Choochart Haruechaiyasak, Wittawat Jitkrittum, Chatchawal Sangkeettrakarn, Chaianun Damrongrat

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.

Choochart Haruechaiyasak, Chatchawal Sangkeettrakarn, Wittawat Jitkrittum

Proceedings of the Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers, 2007