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2020 – today
- 2024
[j35]Tomoharu Iwata
, Atsutoshi Kumagai:
Meta-learning to calibrate Gaussian processes with deep kernels for regression uncertainty estimation. Neurocomputing 579: 127441 (2024)- [j34]Tomoharu Iwata, Yoichi Chikahara:
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers. Mach. Learn. 113(9): 6093-6114 (2024) - [c122]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Zero-Shot Task Adaptation with Relevant Feature Information. AAAI 2024: 13283-13291 - [c121]Yuya Yoshikawa, Tomoharu Iwata:
Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers. AISTATS 2024: 370-378 - [c120]Futoshi Futami, Tomoharu Iwata:
Information-theoretic Analysis of Bayesian Test Data Sensitivity. AISTATS 2024: 1099-1107 - [c119]Masahiro Nakano, Hiroki Sakuma, Ryo Nishikimi, Ryohei Shibue, Takashi Sato, Tomoharu Iwata, Kunio Kashino:
Warped Diffusion for Latent Differentiation Inference. AISTATS 2024: 4789-4797 - [c118]Tomoharu Iwata, Ryo Nishikimi, Ryohei Shibue, Masahiro Nakano, Kunio Kashino, Hitonobu Tomoike:
Electrocardiographic Classification using Deep Learning with Lead Switching. EMBC 2024: 1-4 - [c117]Tomoharu Iwata, Yusuke Tanaka:
Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics. IJCAI 2024: 4210-4218 - [i59]Yoshiaki Takimoto, Yusuke Tanaka, Tomoharu Iwata, Maya Okawa, Hideaki Kim, Hiroyuki Toda, Takeshi Kurashima:
Meta-Learning for Neural Network-based Temporal Point Processes. CoRR abs/2401.15846 (2024) - [i58]Yusuke Tanaka, Takaharu Yaguchi, Tomoharu Iwata, Naonori Ueda:
Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs. CoRR abs/2402.09018 (2024) - [i57]Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuki Yamanaka:
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data. CoRR abs/2405.18929 (2024) - [i56]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Meta-learning for Positive-unlabeled Classification. CoRR abs/2406.03680 (2024) - [i55]Yuka Hashimoto, Tomoharu Iwata:
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices. CoRR abs/2410.02199 (2024) - 2023
- [j33]Tomoharu Iwata:
Meta-learning representations for clustering with infinite Gaussian mixture models. Neurocomputing 549: 126423 (2023) - [j32]Yuya Yoshikawa, Tomoharu Iwata:
Gaussian Process Regression With Interpretable Sample-Wise Feature Weights. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5789-5803 (2023) - [c116]Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara:
Meta-learning for Robust Anomaly Detection. AISTATS 2023: 675-691 - [c115]Hitoshi Shimizu, Hirohiko Suwa, Tomoharu Iwata, Akinori Fujino, Hiroshi Sawada, Keiichi Yasumoto:
School Families: A New Formulation of School District Planning Problem. HICSS 2023: 5122-5131 - [c114]Takeshi Kurashima, Tomoharu Iwata, Tomu Tominaga, Shuhei Yamamoto, Hiroyuki Toda, Kazuhisa Takemura:
Personal History Affects Reference Points: A Case Study of Codeforces. ICWSM 2023: 507-518 - [i54]Tomoharu Iwata, Yoichi Chikahara:
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers. CoRR abs/2305.11353 (2023) - [i53]Futoshi Futami, Tomoharu Iwata:
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty. CoRR abs/2307.12456 (2023) - [i52]Yuya Yoshikawa, Tomoharu Iwata:
Explanation-Based Training with Differentiable Insertion/Deletion Metric-Aware Regularizers. CoRR abs/2310.12553 (2023) - [i51]Tomoharu Iwata, Yusuke Tanaka, Naonori Ueda:
Meta-learning of Physics-informed Neural Networks for Efficiently Solving Newly Given PDEs. CoRR abs/2310.13270 (2023) - [i50]Tomoharu Iwata, Atsutoshi Kumagai:
Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces. CoRR abs/2311.05088 (2023) - [i49]Tomoharu Iwata, Atsutoshi Kumagai:
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation. CoRR abs/2312.07952 (2023) - 2022
- [j31]Israr Ul Haq, Tomoharu Iwata, Yoshinobu Kawahara:
Dynamic mode decomposition via convolutional autoencoders for dynamics modeling in videos. Comput. Vis. Image Underst. 216: 103355 (2022) - [j30]Naohiro Tawara, Atsunori Ogawa, Tomoharu Iwata, Hiroto Ashikawa, Tetsunori Kobayashi, Tetsuji Ogawa:
Multi-Source Domain Generalization Using Domain Attributes for Recurrent Neural Network Language Models. IEICE Trans. Inf. Syst. 105-D(1): 150-160 (2022) - [j29]Yuya Yoshikawa, Tomoharu Iwata:
Neural generators of sparse local linear models for achieving both accuracy and interpretability. Inf. Fusion 81: 116-128 (2022) - [j28]Tomoharu Iwata, Yusuke Tanaka:
Few-shot learning for spatial regression via neural embedding-based Gaussian processes. Mach. Learn. 111(4): 1239-1257 (2022) - [j27]Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Hisashi Kashima:
Context-aware spatio-temporal event prediction via convolutional Hawkes processes. Mach. Learn. 111(8): 2929-2950 (2022) - [j26]Tomoharu Iwata, Hitoshi Shimizu, Naoki Marumo:
Probabilistic Pedestrian Models for Estimating Unobserved Road Populations. IEEE Trans. Intell. Transp. Syst. 23(4): 3037-3047 (2022) - [c113]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama:
Predictive variational Bayesian inference as risk-seeking optimization. AISTATS 2022: 5051-5083 - [c112]Hitoshi Shimizu, Hirohiko Suwa, Tomoharu Iwata, Akinori Fujino, Hiroshi Sawada, Keiichi Yasumoto:
Evacuation Shelter Scheduling Problem. HICSS 2022: 1-10 - [c111]Keisuke Kinoshita, Marc Delcroix, Tomoharu Iwata:
Tight Integration Of Neural- And Clustering-Based Diarization Through Deep Unfolding Of Infinite Gaussian Mixture Model. ICASSP 2022: 8382-8386 - [c110]Atsutoshi Kumagai, Tomoharu Iwata, Taishi Nishiyama, Yasuhiro Fujiwara:
Transfer Anomaly Detection for Maximizing the Partial AUC. IJCNN 2022: 1-8 - [c109]Maya Okawa, Tomoharu Iwata:
Predicting Opinion Dynamics via Sociologically-Informed Neural Networks. KDD 2022: 1306-1316 - [c108]Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima:
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. KDD 2022: 1739-1748 - [c107]Yusuke Tanaka, Tomoharu Iwata, Naonori Ueda:
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data. NeurIPS 2022 - [c106]Tomoharu Iwata, Atsutoshi Kumagai:
Sharing Knowledge for Meta-learning with Feature Descriptions. NeurIPS 2022 - [c105]Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara:
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion. NeurIPS 2022 - [i48]Keisuke Kinoshita, Marc Delcroix, Tomoharu Iwata:
Tight integration of neural- and clustering-based diarization through deep unfolding of infinite Gaussian mixture model. CoRR abs/2202.06524 (2022) - [i47]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama:
Excess risk analysis for epistemic uncertainty with application to variational inference. CoRR abs/2206.01606 (2022) - [i46]Tomoharu Iwata, Atsutoshi Kumagai:
Meta-learning for Out-of-Distribution Detection via Density Estimation in Latent Space. CoRR abs/2206.09543 (2022) - [i45]Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda:
Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains. CoRR abs/2206.12141 (2022) - [i44]Maya Okawa, Tomoharu Iwata:
Predicting Opinion Dynamics via Sociologically-Informed Neural Networks. CoRR abs/2207.03990 (2022) - [i43]Tomoharu Iwata, Yoshinobu Kawahara:
Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces. CoRR abs/2208.08883 (2022) - [i42]Tomoharu Iwata:
Active Learning for Regression with Aggregated Outputs. CoRR abs/2210.01329 (2022) - [i41]Shuhei A. Horiguchi, Tomoharu Iwata, Taku Tsuzuki, Yosuke Ozawa:
Linear Embedding-based High-dimensional Batch Bayesian Optimization without Reconstruction Mappings. CoRR abs/2211.00947 (2022) - [i40]Tomoharu Iwata, Yoshinobu Kawahara:
Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies. CoRR abs/2212.13033 (2022) - 2021
- [j25]Yusuke Tanaka, Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda, Naonori Ueda, Toshiyuki Tanaka:
Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations. Artif. Intell. 292: 103430 (2021) - [j24]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato:
Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices. Entropy 23(8): 993 (2021) - [c104]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane:
Skew-symmetrically perturbed gradient flow for convex optimization. ACML 2021: 721-736 - [c103]Tomoharu Iwata, Yoshinobu Kawahara:
Controlling Nonlinear Dynamical Systems with Linear Quadratic Regulator-based Policy Networks in Koopman space. CDC 2021: 5086-5091 - [c102]Makoto Morishita, Jun Suzuki, Tomoharu Iwata, Masaaki Nagata:
Context-aware Neural Machine Translation with Mini-batch Embedding. EACL 2021: 2513-2521 - [c101]Ryohei Shibue, Masahiro Nakano, Tomoharu Iwata, Kunio Kashino, Hitonobu Tomoike:
Unsupervised Heart Sound Decomposition and State Estimation with Generative Oscillation Models. EMBC 2021: 5481-5487 - [c100]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Semi-supervised Anomaly Detection on Attributed Graphs. IJCNN 2021: 1-8 - [c99]Kengo Tajiri, Tomoharu Iwata, Yoichi Matsuo, Keishiro Watanabe:
Fault Detection of ICT systems with Deep Learning Model for Missing Data. IM 2021: 445-451 - [c98]Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima:
Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. KDD 2021: 1276-1286 - [c97]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama:
Loss function based second-order Jensen inequality and its application to particle variational inference. NeurIPS 2021: 6803-6815 - [c96]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Meta-Learning for Relative Density-Ratio Estimation. NeurIPS 2021: 30426-30438 - [i39]Masanori Yamada, Sekitoshi Kanai, Tomoharu Iwata, Tomokatsu Takahashi, Yuki Yamanaka, Hiroshi Takahashi, Atsutoshi Kumagai:
Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression. CoRR abs/2102.02950 (2021) - [i38]Tomoharu Iwata, Yoshinobu Kawahara:
Meta-Learning for Koopman Spectral Analysis with Short Time-series. CoRR abs/2102.04683 (2021) - [i37]Tomoharu Iwata, Atsutoshi Kumagai:
Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection. CoRR abs/2103.00684 (2021) - [i36]Tomoharu Iwata:
Meta-learning representations for clustering with infinite Gaussian mixture models. CoRR abs/2103.00694 (2021) - [i35]Tomoharu Iwata:
Few-shot Learning for Topic Modeling. CoRR abs/2104.09011 (2021) - [i34]Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima:
Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. CoRR abs/2105.11152 (2021) - [i33]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama:
Loss function based second-order Jensen inequality and its application to particle variational inference. CoRR abs/2106.05010 (2021) - [i32]Tomoharu Iwata:
Meta-learning for Matrix Factorization without Shared Rows or Columns. CoRR abs/2106.15133 (2021) - [i31]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Meta-Learning for Relative Density-Ratio Estimation. CoRR abs/2107.00801 (2021) - [i30]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Few-shot Learning for Unsupervised Feature Selection. CoRR abs/2107.00816 (2021) - [i29]Tomoharu Iwata:
End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian Optimization. CoRR abs/2111.00639 (2021) - [i28]Hitoshi Shimizu, Hirohiko Suwa, Tomoharu Iwata, Akinori Fujino, Hiroshi Sawada, Keiichi Yasumoto:
Evacuation Shelter Scheduling Problem. CoRR abs/2111.13326 (2021) - [i27]Tomoharu Iwata, Yuya Yoshikawa:
Training Deep Models to be Explained with Fewer Examples. CoRR abs/2112.03508 (2021) - 2020
- [j23]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Transfer Metric Learning for Unseen Domains. Data Sci. Eng. 5(2): 140-151 (2020) - [j22]Tomoharu Iwata, Machiko Toyoda, Shotaro Tora, Naonori Ueda:
Anomaly detection with inexact labels. Mach. Learn. 109(8): 1617-1633 (2020) - [c95]Tomoharu Iwata, Akinori Fujino, Naonori Ueda:
Semi-Supervised Learning for Maximizing the Partial AUC. AAAI 2020: 4239-4246 - [c94]Tomoharu Iwata, Naoki Marumo:
Co-Occurrence Estimation from Aggregated Data with Auxiliary Information. AAAI 2020: 4247-4254 - [c93]Masanori Yamada, Heecheol Kim, Kosuke Miyoshi, Tomoharu Iwata, Hiroshi Yamakawa:
Disentangled Representations for Sequence Data using Information Bottleneck Principle. ACML 2020: 305-320 - [c92]Yosuke Higuchi, Naohiro Tawara, Atsunori Ogawa, Tomoharu Iwata, Tetsunori Kobayashi, Tetsuji Ogawa:
Noise-robust Attention Learning for End-to-End Speech Recognition. EUSIPCO 2020: 311-315 - [c91]Naohiro Tawara, Atsunori Ogawa, Tomoharu Iwata, Marc Delcroix, Tetsuji Ogawa:
Frame-Level Phoneme-Invariant Speaker Embedding for Text-Independent Speaker Recognition on Extremely Short Utterances. ICASSP 2020: 6799-6803 - [c90]Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima:
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. ICML 2020: 4594-4603 - [c89]Heecheol Kim, Masanori Yamada, Kosuke Miyoshi, Tomoharu Iwata, Hiroshi Yamakawa:
Reinforcement Learning in Latent Action Sequence Space. IROS 2020: 5497-5503 - [c88]Tomoharu Iwata, Atsutoshi Kumagai:
Meta-learning from Tasks with Heterogeneous Attribute Spaces. NeurIPS 2020 - [c87]Hitoshi Shimizu, Takanori Hara, Tomoharu Iwata:
Deep Reinforcement Learning for Pedestrian Guidance. PRIMA 2020: 334-342 - [i26]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Semi-supervised Anomaly Detection on Attributed Graphs. CoRR abs/2002.12011 (2020) - [i25]Yuya Yoshikawa, Tomoharu Iwata:
Neural Generators of Sparse Local Linear Models for Achieving both Accuracy and Interpretability. CoRR abs/2003.06441 (2020) - [i24]Yasunori Akagi, Yusuke Tanaka, Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda:
Probabilistic Optimal Transport based on Collective Graphical Models. CoRR abs/2006.08866 (2020) - [i23]Yuya Yoshikawa, Tomoharu Iwata:
Gaussian Process Regression with Local Explanation. CoRR abs/2007.01669 (2020) - [i22]Tomoharu Iwata, Atsutoshi Kumagai:
Few-shot Learning for Time-series Forecasting. CoRR abs/2009.14379 (2020) - [i21]Tomoharu Iwata, Yusuke Tanaka:
Few-shot Learning for Spatial Regression. CoRR abs/2010.04360 (2020) - [i20]Tomoharu Iwata:
Meta-Active Learning for Node Response Prediction in Graphs. CoRR abs/2010.05387 (2020) - [i19]Takashi Wada, Tomoharu Iwata, Yuji Matsumoto, Timothy Baldwin, Jey Han Lau:
Learning Contextualised Cross-lingual Word Embeddings for Extremely Low-Resource Languages Using Parallel Corpora. CoRR abs/2010.14649 (2020) - [i18]Tomoharu Iwata, Yoshinobu Kawahara:
Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics. CoRR abs/2012.06191 (2020)
2010 – 2019
- 2019
- [j21]Michael Hentschel, Marc Delcroix, Atsunori Ogawa, Tomoharu Iwata, Tomohiro Nakatani:
Feature Based Domain Adaptation for Neural Network Language Models with Factorised Hidden Layers. IEICE Trans. Inf. Syst. 102-D(3): 598-608 (2019) - [c86]Tomoharu Iwata, Hitoshi Shimizu:
Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data. AAAI 2019: 3935-3942 - [c85]Atsutoshi Kumagai, Tomoharu Iwata:
Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations. AAAI 2019: 4106-4113 - [c84]Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi:
Variational Autoencoder with Implicit Optimal Priors. AAAI 2019: 5066-5073 - [c83]Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa, Hiroyuki Toda:
Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities. AAAI 2019: 5091-5099 - [c82]Takashi Wada, Tomoharu Iwata, Yuji Matsumoto:
Unsupervised Multilingual Word Embedding with Limited Resources using Neural Language Models. ACL (1) 2019: 3113-3124 - [c81]Shigeki Karita, Shinji Watanabe, Tomoharu Iwata, Marc Delcroix, Atsunori Ogawa, Tomohiro Nakatani:
Semi-supervised End-to-end Speech Recognition Using Text-to-speech and Autoencoders. ICASSP 2019: 6166-6170 - [c80]Michael Hentschel, Marc Delcroix, Atsunori Ogawa, Tomoharu Iwata, Tomohiro Nakatani:
A Unified Framework for Feature-based Domain Adaptation of Neural Network Language Models. ICASSP 2019: 7250-7254 - [c79]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Transfer Metric Learning for Unseen Domains. ICDM 2019: 1168-1173 - [c78]Takuma Otsuka, Hitoshi Shimizu, Tomoharu Iwata, Futoshi Naya, Hiroshi Sawada, Naonori Ueda:
Bayesian Optimization for Crowd Traffic Control Using Multi-Agent Simulation. ITSC 2019: 1981-1988 - [c77]Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda:
Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. KDD 2019: 373-383 - [c76]Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Transfer Anomaly Detection by Inferring Latent Domain Representations. NeurIPS 2019: 2467-2477 - [c75]Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda:
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs. NeurIPS 2019: 3000-3010 - [c74]Yuki Yamanaka, Tomoharu Iwata, Hiroshi Takahashi, Masanori Yamada, Sekitoshi Kanai:
Autoencoding Binary Classifiers for Supervised Anomaly Detection. PRICAI (2) 2019: 647-659 - [i17]Yuki Yamanaka, Tomoharu Iwata, Hiroshi Takahashi, Masanori Yamada, Sekitoshi Kanai:
Autoencoding Binary Classifiers for Supervised Anomaly Detection. CoRR abs/1903.10709 (2019) - [i16]Tomoharu Iwata, Yuki Yamanaka:
Supervised Anomaly Detection based on Deep Autoregressive Density Estimators. CoRR abs/1904.06034 (2019) - [i15]Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda:
Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. CoRR abs/1906.08952 (2019) - [i14]Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda:
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs. CoRR abs/1907.08350 (2019) - [i13]Tomoharu Iwata, Machiko Toyoda, Shotaro Tora, Naonori Ueda:
Anomaly Detection with Inexact Labels. CoRR abs/1909.04807 (2019) - [i12]Tomoharu Iwata, Takuma Otsuka:
Efficient Transfer Bayesian Optimization with Auxiliary Information. CoRR abs/1909.07670 (2019) - 2018
- [j20]Tomoharu Iwata, Tsutomu Hirao, Naonori Ueda:
Topic Models for Unsupervised Cluster Matching. IEEE Trans. Knowl. Data Eng. 30(4): 786-795 (2018) - [c73]Michael Hentschel, Marc Delcroix, Atsunori Ogawa, Tomoharu Iwata, Tomohiro Nakatani:
Factorised Hidden Layer Based Domain Adaptation for Recurrent Neural Network Language Models. APSIPA 2018: 1940-1944 - [c72]Akisato Kimura, Zoubin Ghahramani, Koh Takeuchi, Tomoharu Iwata, Naonori Ueda:
Few-shot learning of neural networks from scratch by pseudo example optimization. BMVC 2018: 105 - [c71]Tsuyoshi Morioka, Naohiro Tawara, Tetsuji Ogawa, Atsunori Ogawa, Tomoharu Iwata, Tetsunori Kobayashi:
Language Model Domain Adaptation Via Recurrent Neural Networks with Domain-Shared and Domain-Specific Representations. ICASSP 2018: 6084-6088 - [c70]Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi:
Student-t Variational Autoencoder for Robust Density Estimation. IJCAI 2018: 2696-2702 - [c69]Yusuke Tanaka, Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda, Naonori Ueda:
Estimating Latent People Flow without Tracking Individuals. IJCAI 2018: 3556-3563 - [c68]Shigeki Karita, Shinji Watanabe, Tomoharu Iwata, Atsunori Ogawa, Marc Delcroix:
Semi-Supervised End-to-End Speech Recognition. INTERSPEECH 2018: 2-6 - [c67]Atsutoshi Kumagai, Tomoharu Iwata:
Learning Dynamics of Decision Boundaries without Additional Labeled Data. KDD 2018: 1627-1636 - [c66]Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima:
On Reducing Dimensionality of Labeled Data Efficiently. PAKDD (3) 2018: 77-88 - [c65]Hitoshi Shimizu, Tatsushi Matsubayashi, Yusuke Tanaka, Tomoharu Iwata, Naonori Ueda, Hiroshi Sawada:
Improving Route Traffic Estimation by Considering Staying Population. PRIMA 2018: 630-637 - [i11]Akisato Kimura, Zoubin Ghahramani, Koh Takeuchi, Tomoharu Iwata, Naonori Ueda:
Imitation networks: Few-shot learning of neural networks from scratch. CoRR abs/1802.03039 (2018) - [i10]