Jitkrittum, Wittawat

30 publications

ICML 2025 Bipartite Ranking from Multiple Labels: On Loss Versus Label Aggregation Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, Mohammadhossein Bateni, Sanjiv Kumar

ICLR 2025 Faster Cascades via Speculative Decoding Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar

NeurIPS 2025 Gatekeeper: Improving Model Cascades Through Confidence Tuning Stephan Rabanser, Nathalie Rauschmayr, Achin Kulshrestha, Petra Poklukar, Wittawat Jitkrittum, Sean Augenstein, Congchao Wang, Federico Tombari

ICLRW 2025 Universal LLM Routing with Correctness-Based Representation Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Jeevesh Juneja, Zifeng Wang, Chen-Yu Lee, Pradeep Shenoy, Rina Panigrahy, Aditya Krishna Menon, Sanjiv Kumar

ICLR 2024 Language Model Cascades: Token-Level Uncertainty and Beyond Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar

ICLR 2024 Learning to Reject Meets Long-Tail Learning Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar

ICLR 2024 On Bias-Variance Alignment in Deep Models Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar

ICLR 2024 Plugin Estimators for Selective Classification with Out-of-Distribution Detection Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar

ICML 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

NeurIPS 2023 When Does Confidence-Based Cascade Deferral Suffice? Wittawat Jitkrittum, Neha Gupta, Aditya K Menon, Harikrishna Narasimhan, Ankit Rawat, Sanjiv Kumar

AISTATS 2022 A Witness Two-Sample Test Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

ECCV 2022 A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch Patsorn Sangkloy, Wittawat Jitkrittum, Diyi Yang, James Hays

NeurIPS 2022 Post-Hoc Estimators for Learning to Defer to an Expert Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya K Menon, Ankit Rawat, Sanjiv Kumar

AISTATS 2021 Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf

ICML 2021 Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces Ankit Singh Rawat, Aditya K Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Yu, Sashank Reddi, Sanjiv Kumar

UAI 2020 Kernel Conditional Moment Test via Maximum Moment Restriction Krikamol Muandet, Wittawat Jitkrittum, Jonas Kübler

NeurIPS 2020 Learning Kernel Tests Without Data Splitting Jonas Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

AISTATS 2020 More Powerful Selective Kernel Tests for Feature Selection Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira

UAI 2020 Testing Goodness of Fit of Conditional Density Models with Kernels Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf

NeurIPS 2019 Fisher Efficient Inference of Intractable Models Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen

ICML 2019 Kernel Mean Matching for Content Addressability of GANs Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf

NeurIPS 2019 Kernel Stein Tests for Multiple Model Comparison Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum

NeurIPS 2018 Informative Features for Model Comparison Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton

NeurIPS 2017 A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton

ICML 2017 An Adaptive Test of Independence with Analytic Kernel Embeddings Wittawat Jitkrittum, Zoltán Szabó, Arthur Gretton

NeurIPS 2016 Interpretable Distribution Features with Maximum Testing Power Wittawat Jitkrittum, Zoltán Szabó, Kacper P Chwialkowski, Arthur Gretton

AISTATS 2016 K2-ABC: Approximate Bayesian Computation with Kernel Embeddings Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic

NeurIPS 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltan Szabo, Lars Buesing, Maneesh Sahani

UAI 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

ICML 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