Kohei Miyaguchi
8 papers · 2019–2024 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (23)
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Grand Slam
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Conference Pioneer
Top co-authors
Research topics
Machine Learning
(8)
Optimization & Theory
(6)
Core Methods
(5)
Learning Types
(4)
Deep Learning
(3)
Reinforcement Learning
(2)
Architectures
(2)
Methods Β· Reinforcement Learning
(2)
Artificial Intelligence
(1)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Core AI
(1)
Methods Β· Data Science & Analytics
(1)
Models
(1)
Keywords
neural network
(2)
stochastic gradient descent
(2)
online learning
(1)
offline reinforcement learning
(1)
discriminative learning
(1)
policy optimization
(1)
bayesian inference
(1)
adaptive learning rate
(1)
sample complexity
(1)
markov decision process
(1)
variational inference
(1)
time series forecasting
(1)
hierarchical model
(1)
statistical estimation
(1)
molecular optimization
(1)
missing value imputation
(1)
minimax regret
(1)
learning rate
(1)
variational autoencoder
(1)
generative modeling
(1)
Papers
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
NeurIPS 2024
Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies
ICML 2023
Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction
IJCAI 2022
Hierarchical Lattice Layer for Partially Monotone Neural Networks
NeurIPS 2022
Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion
ICLR 2022
Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models
NeurIPS 2021
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity
AISTATS 2019
Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting
AAAI 2019