Masaaki Imaizumi
18 papers · 2016–2026 · 9 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π§ Keyword Pioneer π Academic Marathon (9) π£ Hot Topic Early Bird
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Cross-Pollinator
(14)
π
Conference Polyglot
(8)
π
Century Club
(17)
π₯
Unstoppable
(10)
ποΈ
Keyword Collector
(59)
Conferences
AISTATS (5)
ICML (3)
ICLR (2)
JMLR (2)
NIPS (2)
ACL (1)
CLEAR (1)
IJCAI (1)
UAI (1)
Top co-authors
Keywords
deep neural network
(3)
tensor decomposition
(3)
non-smooth function
(2)
nonparametric regression
(2)
approximation error
(2)
generalization error
(2)
minimax optimality
(1)
kl divergence
(1)
convex optimization
(1)
maximum likelihood
(1)
bayesian estimation
(1)
policy search
(1)
convex relaxation
(1)
gaussian process regression
(1)
low-rank approximation
(1)
density estimation
(1)
density ratio estimation
(1)
marginal likelihood
(1)
high-dimensional regression
(1)
partially observable markov decision process
(1)
Papers
Why Mean Pooling Works: Quantifying Second-Order Collapse in Text Embeddings
ACL 2026
Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient Descent
AISTATS 2025
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
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
ICLR 2024
Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics
AISTATS 2023
High-dimensional Contextual Bandit Problem without Sparsity
NIPS 2023
Learning Causal Models from Conditional Moment Restrictions by Importance Weighting
ICLR 2022
Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces
JMLR 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
Tensor Decomposition with Smoothness
ICML 2017
On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm
NIPS 2017
Doubly Decomposing Nonparametric Tensor Regression
ICML 2016