Takashi Takenouchi
9 papers · 2015–2022 · 7 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (26) 🌍 Conference Polyglot · Silver
🏆
Keyword Champion
(2)
🚀
Conference Pioneer
🗃️
Keyword Collector
(53)
Top co-authors
Research topics
Machine Learning
(9)
Learning Types
(6)
Artificial Intelligence
(4)
Core Methods
(4)
Optimization & Theory
(4)
Application Areas
(3)
Mathematics & Optimization
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Core AI
(1)
Learning Paradigms
(1)
Mathematics
(1)
Optimization
(1)
Keywords
representation learning
(2)
unnormalized model
(2)
nonlinear independent component analysis
(2)
contrastive learning
(2)
normalization constant
(2)
variational inference
(1)
weakly supervised learning
(1)
divergence minimization
(1)
causal discovery
(1)
parameter estimation
(1)
statistical inference
(1)
adversarial training
(1)
bregman divergence
(1)
mutual information
(1)
asymptotic variance
(1)
logistic regression
(1)
density ratio estimation
(1)
robust estimation
(1)
maximum likelihood estimation
(1)
label noise
(1)
Papers
Representation Learning for Maximization of MI, Nonlinear ICA and Nonlinear Subspaces with Robust Density Ratio Estimation
JMLR 2022
Lower-Bounded Proper Losses for Weakly Supervised Classification
ICML 2021
Regret Minimization for Causal Inference on Large Treatment Space
AISTATS 2021
A Unified Statistically Efficient Estimation Framework for Unnormalized Models
AISTATS 2020
Partially Zero-shot Domain Adaptation from Incomplete Target Data with Missing Classes
WACV 2020
Robust contrastive learning and nonlinear ICA in the presence of outliers
UAI 2020
Zero-shot Domain Adaptation Based on Attribute Information
ACML 2019
Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences
JMLR 2017
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces
NeurIPS 2015