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Importance Weighting for Transfer Learning
Masashi Sugiyama
Mon Dec 13 03:50 PM -- 04:15 PM (PST) @
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Masashi Sugiyama (RIKEN / University of Tokyo)
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2021 : On the Role of Pre-training for Meta Few-Shot Learning »
Chia-You Chen · Hsuan-Tien Lin · Masashi Sugiyama · Gang Niu -
2022 Poster: Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses »
Yuzhou Cao · Tianchi Cai · Lei Feng · Lihong Gu · Jinjie GU · Bo An · Gang Niu · Masashi Sugiyama -
2022 Poster: Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks »
Jianan Zhou · Jianing Zhu · Jingfeng ZHANG · Tongliang Liu · Gang Niu · Bo Han · Masashi Sugiyama -
2023 Poster: Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization »
Xilie Xu · Jingfeng ZHANG · Feng Liu · Masashi Sugiyama · Mohan Kankanhalli -
2023 Poster: On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective »
Zeke Xie · Zhiqiang Xu · Jingzhao Zhang · Issei Sato · Masashi Sugiyama -
2023 Poster: Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution »
Xin-Qiang Cai · Pushi Zhang · Li Zhao · Jiang Bian · Masashi Sugiyama · Ashley Llorens -
2023 Poster: Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost »
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2023 Poster: Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection »
Xilie Xu · Jingfeng ZHANG · Feng Liu · Masashi Sugiyama · Mohan Kankanhalli -
2023 Poster: Adapting to Continuous Covariate Shift via Online Density Ratio Estimation »
Yu-Jie Zhang · Zhen-Yu Zhang · Peng Zhao · Masashi Sugiyama -
2023 Poster: Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning »
Ming-Kun Xie · Jiahao Xiao · Hao-Zhe Liu · Gang Niu · Masashi Sugiyama · Sheng-Jun Huang -
2023 Poster: Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation »
Jianing Zhu · Geng Yu · Jiangchao Yao · Tongliang Liu · Gang Niu · Masashi Sugiyama · Bo Han -
2023 Poster: Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems »
Tongtong Fang · Nan Lu · Gang Niu · Masashi Sugiyama -
2023 Poster: Imitation Learning from Vague Feedback »
Xin-Qiang Cai · Yu-Jie Zhang · Chao-Kai Chiang · Masashi Sugiyama -
2023 Poster: Binary Classification with Confidence Difference »
Wei Wang · Lei Feng · Yuchen Jiang · Gang Niu · Min-Ling Zhang · Masashi Sugiyama -
2023 Workshop: Workshop on Distribution Shifts: New Frontiers with Foundation Models »
Rebecca Roelofs · Fanny Yang · Hongseok Namkoong · Masashi Sugiyama · Jacob Eisenstein · Pang Wei Koh · Shiori Sagawa · Tatsunori Hashimoto · Yoonho Lee -
2022 Spotlight: Lightning Talks 6A-4 »
Xiu-Shen Wei · Konstantina Dritsa · Guillaume Huguet · ABHRA CHAUDHURI · Zhenbin Wang · Kevin Qinghong Lin · Yutong Chen · Jianan Zhou · Yongsen Mao · Junwei Liang · Jinpeng Wang · Mao Ye · Yiming Zhang · Aikaterini Thoma · H.-Y. Xu · Daniel Sumner Magruder · Enwei Zhang · Jianing Zhu · Ronglai Zuo · Massimiliano Mancini · Hanxiao Jiang · Jun Zhang · Fangyun Wei · Faen Zhang · Ioannis Pavlopoulos · Zeynep Akata · Xiatian Zhu · Jingfeng ZHANG · Alexander Tong · Mattia Soldan · Chunhua Shen · Yuxin Peng · Liuhan Peng · Michael Wray · Tongliang Liu · Anjan Dutta · Yu Wu · Oluwadamilola Fasina · Panos Louridas · Angel Chang · Manik Kuchroo · Manolis Savva · Shujie LIU · Wei Zhou · Rui Yan · Gang Niu · Liang Tian · Bo Han · Eric Z. XU · Guy Wolf · Yingying Zhu · Brian Mak · Difei Gao · Masashi Sugiyama · Smita Krishnaswamy · Rong-Cheng Tu · Wenzhe Zhao · Weijie Kong · Chengfei Cai · WANG HongFa · Dima Damen · Bernard Ghanem · Wei Liu · Mike Zheng Shou -
2022 Spotlight: Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks »
Jianan Zhou · Jianing Zhu · Jingfeng ZHANG · Tongliang Liu · Gang Niu · Bo Han · Masashi Sugiyama -
2022 Workshop: Workshop on Distribution Shifts: Connecting Methods and Applications »
Chelsea Finn · Fanny Yang · Hongseok Namkoong · Masashi Sugiyama · Jacob Eisenstein · Jonas Peters · Rebecca Roelofs · Shiori Sagawa · Pang Wei Koh · Yoonho Lee -
2022 Poster: Adapting to Online Label Shift with Provable Guarantees »
Yong Bai · Yu-Jie Zhang · Peng Zhao · Masashi Sugiyama · Zhi-Hua Zhou -
2022 Poster: Fast and Robust Rank Aggregation against Model Misspecification »
YUANGANG PAN · Ivor W. Tsang · Weijie Chen · Gang Niu · Masashi Sugiyama -
2022 Poster: Synergy-of-Experts: Collaborate to Improve Adversarial Robustness »
Sen Cui · Jingfeng ZHANG · Jian Liang · Bo Han · Masashi Sugiyama · Changshui Zhang -
2022 Poster: Learning Contrastive Embedding in Low-Dimensional Space »
Shuo Chen · Chen Gong · Jun Li · Jian Yang · Gang Niu · Masashi Sugiyama -
2021 Workshop: Second Workshop on Quantum Tensor Networks in Machine Learning »
Xiao-Yang Liu · Qibin Zhao · Ivan Oseledets · Yufei Ding · Guillaume Rabusseau · Jean Kossaifi · Khadijeh Najafi · Anwar Walid · Andrzej Cichocki · Masashi Sugiyama -
2021 : Discussion: Chelsea Finn, Masashi Sugiyama »
Chelsea Finn · Masashi Sugiyama -
2021 Poster: Loss function based second-order Jensen inequality and its application to particle variational inference »
Futoshi Futami · Tomoharu Iwata · naonori ueda · Issei Sato · Masashi Sugiyama -
2021 Poster: Probabilistic Margins for Instance Reweighting in Adversarial Training »
qizhou wang · Feng Liu · Bo Han · Tongliang Liu · Chen Gong · Gang Niu · Mingyuan Zhou · Masashi Sugiyama -
2020 Poster: Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning »
Yu Yao · Tongliang Liu · Bo Han · Mingming Gong · Jiankang Deng · Gang Niu · Masashi Sugiyama -
2020 Poster: Part-dependent Label Noise: Towards Instance-dependent Label Noise »
Xiaobo Xia · Tongliang Liu · Bo Han · Nannan Wang · Mingming Gong · Haifeng Liu · Gang Niu · Dacheng Tao · Masashi Sugiyama -
2020 Spotlight: Part-dependent Label Noise: Towards Instance-dependent Label Noise »
Xiaobo Xia · Tongliang Liu · Bo Han · Nannan Wang · Mingming Gong · Haifeng Liu · Gang Niu · Dacheng Tao · Masashi Sugiyama -
2020 Poster: Rethinking Importance Weighting for Deep Learning under Distribution Shift »
Tongtong Fang · Nan Lu · Gang Niu · Masashi Sugiyama -
2020 Poster: Learning from Aggregate Observations »
Yivan Zhang · Nontawat Charoenphakdee · Zhenguo Wu · Masashi Sugiyama -
2020 Poster: Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring »
Taira Tsuchiya · Junya Honda · Masashi Sugiyama -
2020 Spotlight: Rethinking Importance Weighting for Deep Learning under Distribution Shift »
Tongtong Fang · Nan Lu · Gang Niu · Masashi Sugiyama -
2020 Poster: Provably Consistent Partial-Label Learning »
Lei Feng · Jiaqi Lv · Bo Han · Miao Xu · Gang Niu · Xin Geng · Bo An · Masashi Sugiyama -
2020 Poster: Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators »
Takeshi Teshima · Isao Ishikawa · Koichi Tojo · Kenta Oono · Masahiro Ikeda · Masashi Sugiyama -
2020 Oral: Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators »
Takeshi Teshima · Isao Ishikawa · Koichi Tojo · Kenta Oono · Masahiro Ikeda · Masashi Sugiyama -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 Poster: Uncoupled Regression from Pairwise Comparison Data »
Ritsugen Jo · Junya Honda · Gang Niu · Masashi Sugiyama -
2019 Poster: Are Anchor Points Really Indispensable in Label-Noise Learning? »
Xiaobo Xia · Tongliang Liu · Nannan Wang · Bo Han · Chen Gong · Gang Niu · Masashi Sugiyama -
2019 Poster: On the Calibration of Multiclass Classification with Rejection »
Chenri Ni · Nontawat Charoenphakdee · Junya Honda · Masashi Sugiyama -
2018 Poster: Binary Classification from Positive-Confidence Data »
Takashi Ishida · Gang Niu · Masashi Sugiyama -
2018 Spotlight: Binary Classification from Positive-Confidence Data »
Takashi Ishida · Gang Niu · Masashi Sugiyama -
2018 Poster: Uplift Modeling from Separate Labels »
Ikko Yamane · Florian Yger · Jamal Atif · Masashi Sugiyama -
2018 Poster: Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces »
Motoya Ohnishi · Masahiro Yukawa · Mikael Johansson · Masashi Sugiyama -
2018 Poster: Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks »
Yusuke Tsuzuku · Issei Sato · Masashi Sugiyama -
2018 Poster: Masking: A New Perspective of Noisy Supervision »
Bo Han · Jiangchao Yao · Gang Niu · Mingyuan Zhou · Ivor Tsang · Ya Zhang · Masashi Sugiyama -
2018 Poster: Co-teaching: Robust training of deep neural networks with extremely noisy labels »
Bo Han · Quanming Yao · Xingrui Yu · Gang Niu · Miao Xu · Weihua Hu · Ivor Tsang · Masashi Sugiyama -
2017 : Poster Session (encompasses coffee break) »
Beidi Chen · Borja Balle · Daniel Lee · iuri frosio · Jitendra Malik · Jan Kautz · Ke Li · Masashi Sugiyama · Miguel A. Carreira-Perpinan · Ramin Raziperchikolaei · Theja Tulabandhula · Yung-Kyun Noh · Adams Wei Yu -
2017 Poster: Positive-Unlabeled Learning with Non-Negative Risk Estimator »
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama -
2017 Poster: Learning from Complementary Labels »
Takashi Ishida · Gang Niu · Weihua Hu · Masashi Sugiyama -
2017 Oral: Positive-Unlabeled Learning with Non-Negative Risk Estimator »
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama -
2017 Poster: Expectation Propagation for t-Exponential Family Using q-Algebra »
Futoshi Futami · Issei Sato · Masashi Sugiyama -
2017 Poster: Generative Local Metric Learning for Kernel Regression »
Yung-Kyun Noh · Masashi Sugiyama · Kee-Eung Kim · Frank Park · Daniel Lee -
2016 Poster: Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning »
Gang Niu · Marthinus Christoffel du Plessis · Tomoya Sakai · Yao Ma · Masashi Sugiyama -
2014 Poster: Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP »
Shinichi Nakajima · Issei Sato · Masashi Sugiyama · Kazuho Watanabe · Hiroko Kobayashi -
2014 Poster: Multitask learning meets tensor factorization: task imputation via convex optimization »
Kishan Wimalawarne · Masashi Sugiyama · Ryota Tomioka -
2014 Poster: Analysis of Learning from Positive and Unlabeled Data »
Marthinus C du Plessis · Gang Niu · Masashi Sugiyama -
2013 Poster: Parametric Task Learning »
Ichiro Takeuchi · Tatsuya Hongo · Masashi Sugiyama · Shinichi Nakajima -
2013 Poster: Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering »
Shinichi Nakajima · Akiko Takeda · S. Derin Babacan · Masashi Sugiyama · Ichiro Takeuchi -
2012 Poster: Perfect Dimensionality Recovery by Variational Bayesian PCA »
Shinichi Nakajima · Ryota Tomioka · Masashi Sugiyama · S. Derin Babacan -
2012 Poster: Density-Difference Estimation »
Masashi Sugiyama · Takafumi Kanamori · Taiji Suzuki · Marthinus C du Plessis · Song Liu · Ichiro Takeuchi -
2011 Poster: Relative Density-Ratio Estimation for Robust Distribution Comparison »
Makoto Yamada · Taiji Suzuki · Takafumi Kanamori · Hirotaka Hachiya · Masashi Sugiyama -
2011 Poster: Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification »
Ichiro Takeuchi · Masashi Sugiyama -
2011 Poster: Analysis and Improvement of Policy Gradient Estimation »
Tingting Zhao · Hirotaka Hachiya · Gang Niu · Masashi Sugiyama -
2011 Poster: Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent »
Shinichi Nakajima · Masashi Sugiyama · S. Derin Babacan -
2010 Spotlight: Global Analytic Solution for Variational Bayesian Matrix Factorization »
Shinichi Nakajima · Masashi Sugiyama · Ryota Tomioka -
2010 Poster: Global Analytic Solution for Variational Bayesian Matrix Factorization »
Shinichi Nakajima · Masashi Sugiyama · Ryota Tomioka -
2008 Poster: Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection »
Takafumi Kanamori · Shohei Hido · Masashi Sugiyama -
2007 Poster: Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation »
Masashi Sugiyama · Shinichi Nakajima · Hisashi Kashima · Paul von Buenau · Motoaki Kawanabe -
2007 Poster: Multi-Task Learning via Conic Programming »
Tsuyoshi Kato · Hisashi Kashima · Masashi Sugiyama · Kiyoshi Asai -
2006 Workshop: Learning when test and training inputs have different distributions »
Joaquin Quiñonero-Candela · Masashi Sugiyama · Anton Schwaighofer · Neil D Lawrence -
2006 Poster: Mixture Regression for Covariate Shift »
Amos Storkey · Masashi Sugiyama