Wittawat Jitkrittum

74 papers A* 16A 7Journal 43Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cost-Aware Routing for Efficient Text-To-Image Generation. Trans. Mach. Learn. Res. Qinchan Li, Kenneth Chen, Changyue Su, Wittawat Jitkrittum, Qi Sun, Patsorn Sangkloy
2025	A*	`conf`	Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. ICML Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, MohammadHossein Bateni, Sanjiv Kumar
2025	J	`jnl`	Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. CoRR Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, MohammadHossein Bateni, Sanjiv Kumar
2025	J	`jnl`	Cost-Aware Routing for Efficient Text-To-Image Generation. CoRR Qinchan Li, Kenneth Chen, Changyue Su, Wittawat Jitkrittum, Qi Sun, Patsorn Sangkloy
2025	A*	`conf`	Faster Cascades via Speculative Decoding. ICLR Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar
2025	J	`jnl`	I Know What I Don't Know: Improving Model Cascades Through Confidence Tuning. CoRR Stephan Rabanser, Nathalie Rauschmayr, Achin Kulshrestha, Petra Poklukar, Wittawat Jitkrittum, Sean Augenstein, Congchao Wang, Federico Tombari
2025	J	`jnl`	Universal Model Routing for Efficient LLM Inference. CoRR Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Jeevesh Juneja, Zifeng Wang, Chen-Yu Lee, Pradeep Shenoy, Rina Panigrahy, Aditya Krishna Menon, Sanjiv Kumar
2024	J	`jnl`	A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. CoRR 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
2024	J	`jnl`	Cascade-Aware Training of Language Models. CoRR Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go
2024	J	`jnl`	Faster Cascades via Speculative Decoding. CoRR Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar
2024	A*	`conf`	Language Model Cascades: Token-Level Uncertainty And Beyond. ICLR Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2024	J	`jnl`	Language Model Cascades: Token-level uncertainty and beyond. CoRR Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2024	A*	`conf`	Learning to Reject Meets Long-tail Learning. ICLR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar
2024	A*	`conf`	On Bias-Variance Alignment in Deep Models. ICLR Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
2024	A*	`conf`	Plugin estimators for selective classification with out-of-distribution detection. ICLR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
2024	A*	`conf`	USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. ICML Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
2023	J	`jnl`	EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. CoRR Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
2023	J	`jnl`	It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models. CoRR Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
2023	J	`jnl`	Learning to reject meets OOD detection: Are all abstentions created equal? CoRR Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
2023	A*	`conf`	When Does Confidence-Based Cascade Deferral Suffice? NeurIPS Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
2023	J	`jnl`	When Does Confidence-Based Cascade Deferral Suffice? CoRR Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
2022	J	`jnl`	A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch. CoRR Patsorn Sangkloy, Wittawat Jitkrittum, Diyi Yang, James Hays
2022	—	`conf`	A Sketch is Worth a Thousand Words: Image Retrieval with Text and Sketch. ECCV (38) Patsorn Sangkloy, Wittawat Jitkrittum, Diyi Yang, James Hays
2022	A	`conf`	A Witness Two-Sample Test. AISTATS Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2022	J	`jnl`	Discussion of 'Multiscale Fisher's Independence Test for Multivariate Dependence'. CoRR Antonin Schrab, Wittawat Jitkrittum, Zoltán Szabó, Dino Sejdinovic, Arthur Gretton
2022	J	`jnl`	ELM: Embedding and Logit Margins for Long-Tail Learning. CoRR Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
2022	A*	`conf`	Post-hoc estimators for learning to defer to an expert. NeurIPS Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
2021	J	`jnl`	ABCDP: Approximate Bayesian Computation with Differential Privacy. Entropy Mijung Park, Margarita Vinaroz, Wittawat Jitkrittum
2021	J	`jnl`	An Optimal Witness Function for Two-Sample Testing. CoRR Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2021	J	`jnl`	Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces. CoRR Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2021	A*	`conf`	Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. ICML Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2021	J	`jnl`	HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation. CoRR Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang
2021	A	`conf`	Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation. AISTATS Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2020	A	`conf`	Kernel Conditional Moment Test via Maximum Moment Restriction. UAI Krikamol Muandet, Wittawat Jitkrittum, Jonas M. Kübler
2020	J	`jnl`	Kernel Conditional Moment Test via Maximum Moment Restriction. CoRR Krikamol Muandet, Wittawat Jitkrittum, Jonas M. Kübler
2020	J	`jnl`	Kernel Distributionally Robust Optimization. CoRR Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2020	A*	`conf`	Learning Kernel Tests Without Data Splitting. NeurIPS Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2020	J	`jnl`	Learning Kernel Tests Without Data Splitting. CoRR Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2020	A	`conf`	More Powerful Selective Kernel Tests for Feature Selection. AISTATS Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira
2020	A	`conf`	Testing Goodness of Fit of Conditional Density Models with Kernels. UAI Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
2020	J	`jnl`	Testing Goodness of Fit of Conditional Density Models with Kernels. CoRR Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
2020	—	`conf`	Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem. CDC Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2020	J	`jnl`	Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem. CoRR Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2019	J	`jnl`	A Kernel Stein Test for Comparing Latent Variable Models. CoRR Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
2019	J	`jnl`	ABCDP: Approximate Bayesian Computation Meets Differential Privacy. CoRR Mijung Park, Wittawat Jitkrittum
2019	A*	`conf`	Fisher Efficient Inference of Intractable Models. NeurIPS Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen
2019	A*	`conf`	Kernel Mean Matching for Content Addressability of GANs. ICML Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf
2019	J	`jnl`	Kernel Mean Matching for Content Addressability of GANs. CoRR Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf
2019	A*	`conf`	Kernel Stein Tests for Multiple Model Comparison. NeurIPS Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum
2019	J	`jnl`	Kernel Stein Tests for Multiple Model Comparison. CoRR Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum
2019	J	`jnl`	More Powerful Selective Kernel Tests for Feature Selection. CoRR Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira
2019	J	`jnl`	Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces. CoRR Arash Mehrjou, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2018	A*	`conf`	Informative Features for Model Comparison. NeurIPS Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
2018	J	`jnl`	Informative Features for Model Comparison. CoRR Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
2018	J	`jnl`	Model Inference with Stein Density Ratio Estimation. CoRR Song Liu, Wittawat Jitkrittum, Carl Henrik Ek
2017	—	`conf`	A Linear-Time Kernel Goodness-of-Fit Test. NIPS Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton
2017	J	`jnl`	A Linear-Time Kernel Goodness-of-Fit Test. CoRR Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton
2017	A*	`conf`	An Adaptive Test of Independence with Analytic Kernel Embeddings. ICML Wittawat Jitkrittum, Zoltán Szabó, Arthur Gretton
2016	J	`jnl`	An Adaptive Test of Independence with Analytic Kernel Embeddings. CoRR Wittawat Jitkrittum, Zoltán Szabó, Arthur Gretton
2016	—	`conf`	Interpretable Distribution Features with Maximum Testing Power. NIPS Wittawat Jitkrittum, Zoltán Szabó, Kacper P. Chwialkowski, Arthur Gretton
2016	J	`jnl`	Interpretable Distribution Features with Maximum Testing Power. CoRR Wittawat Jitkrittum, Zoltán Szabó, Kacper Chwialkowski, Arthur Gretton
2016	A	`conf`	K2-ABC: Approximate Bayesian Computation with Kernel Embeddings. AISTATS Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
2015	—	`conf`	Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM). NIPS Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó, Lars Buesing, Maneesh Sahani
2015	J	`jnl`	K2-ABC: Approximate Bayesian Computation with Kernel Embeddings. CoRR Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
2015	A	`conf`	Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages. UAI Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó
2015	J	`jnl`	Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages. CoRR Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó
2015	J	`jnl`	Passing Expectation Propagation Messages with Kernel Methods. CoRR Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess
2014	J	`jnl`	High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso. Neural Comput. Makoto Yamada, Wittawat Jitkrittum, Leonid Sigal, Eric P. Xing, Masashi Sugiyama
2013	J	`jnl`	Feature Selection via l IEICE Trans. Inf. Syst. Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama
2013	—	`conf`	Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning. ICML (3) Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama
2012	J	`jnl`	Feature Selection via L1-Penalized Squared-Loss Mutual Information CoRR Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama
2012	J	`jnl`	High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso CoRR Makoto Yamada, Wittawat Jitkrittum, Leonid Sigal, Masashi Sugiyama
2008	—	`conf`	Implementing News Article Category Browsing Based on Text Categorization Technique. Web Intelligence/IAT Workshops Choochart Haruechaiyasak, Wittawat Jitkrittum, Chatchawal Sangkeettrakarn, Chaianun Damrongrat
2007	—	`conf`	Managing Offline Educational Web Contents with Search Engine Tools. ICADL Choochart Haruechaiyasak, Chatchawal Sangkeettrakarn, Wittawat Jitkrittum