← Authors

Tomoharu Iwata

53 papers · 2009–2025 · 11 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (16) πŸ—ΊοΈ Taxonomy Completionist (17) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (16) πŸ† Grand Slam πŸ”¬ Deep Specialist (12) πŸ† Keyword Champion (2) πŸ”₯ Unstoppable (13) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (206) ⚑ Prolific Year (5) πŸ’Ž Century Club (53) πŸ“ˆ 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

Atsutoshi Kumagai (16) Yasuhiro Fujiwara (11) Naonori Ueda (10) Hiroshi Takahashi (7) Yusuke Tanaka (6) Futoshi Futami (4) Yasutoshi Ida (4) Masanori Yamada (3) Takeshi Kurashima (3) Yuya Yoshikawa (3)

Keywords

bayesian inference (6) transfer learning (6) gaussian process (5) few-shot learning (5) probabilistic modeling (5) latent variable model (4) neural network (4) anomaly detection (3) feature selection (3) variational autoencoder (3) latent variable (3) semi-supervised learning (3) variational inference (2) binary classification (2) word alignment (2) positive unlabeled learning (2) distribution shift (2) uncertainty quantification (2) convex optimization (2) information theory (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