Tomoharu Iwata
53 papers · 2009–2025 · 11 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (17) π Renaissance Researcher (6) π Interdisciplinary Bridge π£ Hot Topic Early Bird
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Academic Marathon
(16)
πΊοΈ
Taxonomy Completionist
(17)
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(3)
π€
Dynamic Duo
(16)
π
Grand Slam
π¬
Deep Specialist
(12)
π
Keyword Champion
(2)
π₯
Unstoppable
(13)
π
Conference Pioneer
ποΈ
Keyword Collector
(206)
β‘
Prolific Year
(5)
π
Century Club
(53)
π
Trend Setter
Conferences
NIPS (15)
AISTATS (12)
AAAI (7)
IJCAI (6)
ICML (4)
ACL (3)
ACML (2)
EACL (1)
EMNLP (1)
ICLR (1)
INTERSPEECH (1)
Top co-authors
Keywords
bayesian inference
(6)
transfer learning
(6)
gaussian process
(5)
few-shot learning
(5)
probabilistic modeling
(5)
latent variable model
(4)
neural network
(4)
feature selection
(3)
semi-supervised learning
(3)
latent variable
(3)
variational autoencoder
(3)
anomaly detection
(3)
binary classification
(2)
word alignment
(2)
cross-lingual embedding
(2)
positive unlabeled learning
(2)
distribution shift
(2)
convex optimization
(2)
density estimation
(2)
variational inference
(2)
Papers
Meta-learning from Heterogeneous Tensors for Few-shot Tensor Completion
AISTATS 2025
Importance-weighted Positive-unlabeled Learning for Distribution Shift Adaptation
AISTATS 2025
Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations
AISTATS 2025
Positive-unlabeled AUC Maximization under Covariate Shift
ICML 2025
K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
ICML 2025
Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
ICML 2025
Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
ICLR 2025
Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression
AISTATS 2025
Information-theoretic Analysis of Bayesian Test Data Sensitivity
AISTATS 2024
Warped Diffusion for Latent Differentiation Inference
AISTATS 2024
AUC Maximization under Positive Distribution Shift
NIPS 2024
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
NIPS 2024
Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics
IJCAI 2024
Zero-Shot Task Adaptation with Relevant Feature Information
AAAI 2024
Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers
AISTATS 2024
Meta-learning for Robust Anomaly Detection
AISTATS 2023
Predictive variational Bayesian inference as risk-seeking optimization
AISTATS 2022
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data
NIPS 2022
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion
NIPS 2022
Sharing Knowledge for Meta-learning with Feature Descriptions
NIPS 2022
Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora
EMNLP 2021
Skew-symmetrically perturbed gradient flow for convex optimization
ACML 2021
Context-aware Neural Machine Translation with Mini-batch Embedding
EACL 2021
Meta-Learning for Relative Density-Ratio Estimation
NIPS 2021
Loss function based second-order Jensen inequality and its application to particle variational inference
NIPS 2021
Meta-learning from Tasks with Heterogeneous Attribute Spaces
NIPS 2020
Disentangled Representations for Sequence Data using Information Bottleneck Principle
ACML 2020
Semi-Supervised Learning for Maximizing the Partial AUC
AAAI 2020
Co-Occurrence Estimation from Aggregated Data with Auxiliary Information
AAAI 2020
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance
ICML 2020
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs
NIPS 2019
Transfer Anomaly Detection by Inferring Latent Domain Representations
NIPS 2019
Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data
AAAI 2019
Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations
AAAI 2019
Variational Autoencoder with Implicit Optimal Priors
AAAI 2019
Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities
AAAI 2019
Unsupervised Multilingual Word Embedding with Limited Resources using Neural Language Models
ACL 2019
Student-t Variational Autoencoder for Robust Density Estimation
IJCAI 2018
Semi-Supervised End-to-End Speech Recognition
INTERSPEECH 2018
Estimating Latent People Flow without Tracking Individuals
IJCAI 2018
Localized Lasso for High-Dimensional Regression
AISTATS 2017
SVD-Based Screening for the Graphical Lasso
IJCAI 2017
Learning Latest Classifiers without Additional Labeled Data
IJCAI 2017
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models
NIPS 2016
Identifying Key Observers to Find Popular Information in Advance
IJCAI 2016
Cross-domain recommendation without shared users or items by sharing latent vector distributions
AISTATS 2015
Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions
NIPS 2015
Latent Support Measure Machines for Bag-of-Words Data Classification
NIPS 2014
Latent Semantic Matching: Application to Cross-language Text Categorization without Alignment Information
ACL 2013
Active Learning for Interactive Visualization
AISTATS 2013
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis
NIPS 2010
Learning Common Grammar from Multilingual Corpus
ACL 2010
Modeling Social Annotation Data with Content Relevance using a Topic Model
NIPS 2009