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Discussion: Chelsea Finn, Masashi Sugiyama
Chelsea Finn · Masashi Sugiyama
Mon Dec 13 04:40 PM -- 05:00 PM (PST) @
Author Information
Chelsea Finn (Stanford)
Masashi Sugiyama (RIKEN / University of Tokyo)
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2022 Poster: Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses »
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2022 : A Control-Centric Benchmark for Video Prediction »
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2022 : Relaxing the Kolmogorov Structure Function for Realistic Computational Constraints »
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2022 : Recommendation for New Drugs with Limited Prescription Data »
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2021 Poster: Noether Networks: meta-learning useful conserved quantities »
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2021 Poster: Autonomous Reinforcement Learning via Subgoal Curricula »
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2020 : QA: Chelsea Finn »
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2020 : Mini-panel discussion 3 - Prioritizing Real World RL Challenges »
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2020 : Invited Talk: Chelsea Finn »
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2020 : Keynote: Chelsea Finn »
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2020 : Invited talk - Underfitting and Uncertainty in Self-Supervised Predictive Models »
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2020 Workshop: Deep Reinforcement Learning »
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2020 Poster: Part-dependent Label Noise: Towards Instance-dependent Label Noise »
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2020 Spotlight: Part-dependent Label Noise: Towards Instance-dependent Label Noise »
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2020 Poster: Gradient Surgery for Multi-Task Learning »
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2020 Poster: Rethinking Importance Weighting for Deep Learning under Distribution Shift »
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2020 Poster: Provably Consistent Partial-Label Learning »
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2020 Poster: Continuous Meta-Learning without Tasks »
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2020 Poster: Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators »
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2019 : Poster Presentations »
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2019 Poster: Language as an Abstraction for Hierarchical Deep Reinforcement Learning »
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2019 Poster: On the Calibration of Multiclass Classification with Rejection »
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2018 Poster: Binary Classification from Positive-Confidence Data »
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2018 Poster: Uplift Modeling from Separate Labels »
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2018 Poster: Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces »
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2018 Poster: Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks »
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2018 Poster: Masking: A New Perspective of Noisy Supervision »
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2018 Poster: Co-teaching: Robust training of deep neural networks with extremely noisy labels »
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2017 : Poster Session (encompasses coffee break) »
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2017 Poster: Positive-Unlabeled Learning with Non-Negative Risk Estimator »
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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 »
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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 »
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2012 Poster: Perfect Dimensionality Recovery by Variational Bayesian PCA »
Shinichi Nakajima · Ryota Tomioka · Masashi Sugiyama · S. Derin Babacan -
2012 Poster: Density-Difference Estimation »
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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 »
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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 »
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2010 Poster: Global Analytic Solution for Variational Bayesian Matrix Factorization »
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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 »
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2007 Poster: Multi-Task Learning via Conic Programming »
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2006 Workshop: Learning when test and training inputs have different distributions »
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2006 Poster: Mixture Regression for Covariate Shift »
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