Masaaki Imaizumi
18 papers · 2016–2026 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (36) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π§¬
Topic Evolution
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(91)
π
Century Club Β· Bronze
π₯
Unstoppable Β· Silver
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Renaissance Researcher
(5)
Top co-authors
Research topics
Keywords
tensor decomposition
(3)
deep neural network
(3)
approximation error
(2)
non-smooth function
(2)
image generation
(2)
density ratio estimation
(2)
generative adversarial network
(2)
generalization error
(2)
nonparametric regression
(2)
convex optimization
(1)
minimax optimality
(1)
sample complexity
(1)
online learning
(1)
marginal likelihood
(1)
feature learning
(1)
kl divergence
(1)
convex relaxation
(1)
optimal transport
(1)
model selection
(1)
policy search
(1)
Papers
Why Mean Pooling Works: Quantifying Second-Order Collapse in Text Embeddings
ACL 2026
Distillation of Discrete Diffusion through Dimensional Correlations
ICML 2025
Encode-Decoder-based GAN for Estimating Counterfactual Outcomes under Sequential Selection Bias and Combinatorial Explosion
CLeaR 2025
Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient Descent
AISTATS 2025
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
ICLR 2024
High-dimensional Contextual Bandit Problem without Sparsity
NeurIPS 2023
Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics
AISTATS 2023
Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces
JMLR 2022
Learning Causal Models from Conditional Moment Restrictions by Importance Weighting
ICLR 2022
Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces
UAI 2021
Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality
JMLR 2020
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
AISTATS 2020
Deep Neural Networks Learn Non-Smooth Functions Effectively
AISTATS 2019
Statistically Efficient Estimation for Non-Smooth Probability Densities
AISTATS 2018
Factorized Asymptotic Bayesian Policy Search for POMDPs
IJCAI 2017
On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm
NeurIPS 2017
Tensor Decomposition with Smoothness
ICML 2017
Doubly Decomposing Nonparametric Tensor Regression
ICML 2016