Shinichi Nakajima
26 papers · 2007–2025 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (67) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Full 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Deep Specialist
(11)
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Grand Slam
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Keyword Champion
(7)
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Dynamic Duo
(12)
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Renaissance Researcher
(5)
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Unstoppable · Bronze
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The Questioner
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Century Club · Bronze
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Trend Setter
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Keyword Collector
(161)
Top co-authors
Research topics
Machine Learning
(23)
Deep Learning
(18)
Core Methods
(17)
Artificial Intelligence
(15)
Optimization & Theory
(15)
Models
(11)
Bayesian & Probabilistic · Machine Learning
(7)
Bayesian & Probabilistic · Artificial Intelligence
(6)
Learning Types · Machine Learning
(6)
Core AI
(5)
Learning Types · Deep Learning
(5)
Mathematics & Optimization
(4)
Learning Paradigms
(4)
Computer Vision
(3)
Architectures
(3)
Keywords
variational inference
(10)
matrix factorization
(7)
variational bayesian
(7)
bayesian inference
(4)
variational bayesian inference
(4)
bayesian learning
(4)
neural network
(3)
generative model
(3)
posterior distribution
(3)
dimensionality recovery
(2)
probabilistic principal component analysis
(2)
global analytic solution
(2)
variational bayesian matrix factorization
(2)
variational bayesian learning
(2)
bayesian estimation
(2)
singular value decomposition
(2)
low-rank approximation
(2)
density estimation
(2)
global optimization
(2)
subspace clustering
(2)
Papers
Multilevel Generative Samplers for Investigating Critical Phenomena
ICLR 2025
Adaptive Observation Cost Control for Variational Quantum Eigensolvers
ICML 2024
Federated Learning over Connected Modes
NeurIPS 2024
Generative Fractional Diffusion Models
NeurIPS 2024
Labeling Neural Representations with Inverse Recognition
NeurIPS 2023
Physics-Informed Bayesian Optimization of Variational Quantum Circuits
NeurIPS 2023
Relevant Walk Search for Explaining Graph Neural Networks
ICML 2023
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing
ICML 2022
NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights
AAAI 2022
Path-Gradient Estimators for Continuous Normalizing Flows
ICML 2022
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance
AAAI 2020
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs
AISTATS 2019
Minimizing Trust Leaks for Robust Sybil Detection
ICML 2017
Condition for Perfect Dimensionality Recovery by Variational Bayesian PCA
JMLR 2015
Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?
AISTATS 2014
Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP
NeurIPS 2014
Global Analytic Solution of Fully-observed Variational Bayesian Matrix Factorization
JMLR 2013
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering
NeurIPS 2013
Parametric Task Learning
NeurIPS 2013
Perfect Dimensionality Recovery by Variational Bayesian PCA
NeurIPS 2012
Probabilistic Low-Rank Subspace Clustering
NeurIPS 2012
Sparse Additive Matrix Factorization for Robust PCA and Its Generalization
ACML 2012
Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent
NeurIPS 2011
Theoretical Analysis of Bayesian Matrix Factorization
JMLR 2011
Global Analytic Solution for Variational Bayesian Matrix Factorization
NeurIPS 2010
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
NeurIPS 2007