COM3-02-52
13 Computing Drive
Singapore 117417
Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos Psaros, Kenji Kawaguchi. PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. In Advances in Neural Information Processing Systems (NeurIPS), 2023.
[pdf] [BibTeX]
Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, Xu Zhao, Min-Yen Kan, Junxian He, Qizhe Xie. Decomposition Enhances Reasoning via Self-Evaluation Guided Decoding. In Advances in Neural Information Processing Systems (NeurIPS), 2023.
[pdf] [BibTeX]
Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua. Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. In Advances in Neural Information Processing Systems (NeurIPS), 2023.
[pdf] [BibTeX]
Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang. Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. In Advances in Neural Information Processing Systems (NeurIPS), 2023.
[pdf] [BibTeX]
Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun. An Information Theory Perspective on Variance-Invariance-Covariance Regularization. In Advances in Neural Information Processing Systems (NeurIPS), 2023.
[pdf] [BibTeX]
Kenji Kawaguchi*, Zhun Deng*, Xu Ji*, Jiaoyang Huang. How Does Information Bottleneck Help Deep Learning? International Conference on Machine Learning (ICML), 2023.
[pdf] [BibTeX]
Yingtian Zou*, Vikas Verma*, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi. MixupE: Understanding and improving mixup from directional derivative perspective. Uncertainty in Artificial Intelligence (UAI), 2023.
[pdf] [BibTeX] [the Best Student Paper Award of UAI 2023]
Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi and Yoshua Bengio.
GFlowOut: Dropout with Generative Flow Networks. International Conference on Machine Learning (ICML), 2023.
[pdf] [BibTeX]
Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf. Discrete Key-Value Bottleneck. International Conference on Machine Learning (ICML), 2023.
[pdf] [BibTeX]
Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang. Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation.
International Conference on Machine Learning (ICML), 2023.
[pdf] [BibTeX]
Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya. Auxiliary Learning as an Asymmetric Bargaining Game.
International Conference on Machine Learning (ICML), 2023.
[pdf] [BibTeX]
Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi. Self-Distillation for Further Pre-training of Transformers. In International Conference on Learning Representations (ICLR), 2023.
[pdf] [BibTeX]
Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron Courville. Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. In International Conference on Learning Representations (ICLR), 2023.
[pdf] [BibTeX] [notable-top-25%]
Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, A.H. Castro Neto, Kostya S. Novoselov and Shuicheng YAN. D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. In International Conference on Learning Representations (ICLR), 2023.
[pdf] [BibTeX] [notable-top-25%]
Dong Bok Lee, Seanie Lee, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha and Sung Ju Hwang. Self-Supervised Set Representation Learning for Unsupervised Meta-Learning. In International Conference on Learning Representations (ICLR), 2023.
[pdf] [BibTeX]
Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang. Robustness Implies Generalization via Data-Dependent Generalization Bounds. International Conference on Machine Learning (ICML), 2022.
[pdf] [BibTeX] [Selected for ICML long presentation (2% accept rate)]
Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya. Multi-Task Learning as a Bargaining Game. International Conference on Machine Learning (ICML), 2022.
[pdf] [BibTeX]
Linjun Zhang*, Zhun Deng*, Kenji Kawaguchi, James Zou. When and How Mixup Improves Calibration. International Conference on Machine Learning (ICML), 2022.
[pdf] [BibTeX]
Kenji Kawaguchi. On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers.
In International Conference on Learning Representations (ICLR), 2021.
[pdf] [BibTeX] [Selected for ICLR Spotlight (5% accept rate)]
Linjun Zhang*, Zhun Deng*, Kenji Kawaguchi*, Amirata Ghorbani and James Zou. How Does Mixup Help With Robustness and Generalization?
In International Conference on Learning Representations (ICLR), 2021.
[pdf] [BibTeX] [Selected for ICLR Spotlight (5% accept rate)]