Hirotaka Hachiya

According to our database, Hirotaka Hachiya authored at least 45 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Specular Surface Detection with Deep Static Specular Flow and Highlight.

Hirotaka Hachiya, Yuto Yoshimura

Mach. Vis. Appl., November, 2024

Set representative vector and its asymmetric attention-based transformation for heterogeneous set-to-set matching.

Hirotaka Hachiya, Yuki Saito

Neurocomputing, 2024

2023

Multistream-Based Marked Point Process With Decomposed Cumulative Hazard Functions.

Hirotaka Hachiya, Sujun Hong

Neural Comput., 2023

Multi-feature subspace representation network for person re-identification via bird's-eye view image.

Jiwei Zhang, Haiyuan Wu, Qian Chen, Hirotaka Hachiya

Comput. Animat. Virtual Worlds, 2023

Combining Static Specular Flow and Highlight with Deep Features for Specular Surface Detection.

Hirotaka Hachiya, Yuto Yoshimura

Proceedings of the 18th International Conference on Machine Vision and Applications, 2023

Frequency-dependent Image Reconstruction Error for Micro Defect Detection.

Yuhei Nomura, Hirotaka Hachiya

Proceedings of the Asian Conference on Machine Learning, 2023

2022

Position-dependent partial convolutions for supervised spatial interpolation.

Hirotaka Hachiya, Kotaro Nagayoshi, Asako Iwaki, Takahiro Maeda, Naonori Ueda, Hiroyuki Fujiwara

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Multi-stream based marked point process.

Sujun Hong, Hirotaka Hachiya

Proceedings of the Asian Conference on Machine Learning, 2021

Encoder-decoder-based image transformation approach for integrating precipitation forecasts.

Hirotaka Hachiya, Yusuke Masumoto, Yuki Mori, Naonori Ueda

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Translation Between Waves, wave2wave.

Tsuyoshi Okita, Hirotaka Hachiya, Sozo Inoue, Naonori Ueda

CoRR, 2020

Exchangeable Deep Neural Networks for Set-to-Set Matching and Learning.

Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Deep Set-to-Set Matching and Learning.

Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu

CoRR, 2019

Adaptive truncated residual regression for fine-grained regression problems.

Hirotaka Hachiya, Yu Yamamoto, Kazuro Hirahara, Naonori Ueda

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

Laser Variational Autoencoder for Map Construction and Self-Localization.

Shohei Wakita, Takayuki Nakamura, Hirotaka Hachiya

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

2.5D Faster R-CNN for Distance Estimation.

Hirotaka Hachiya, Yuki Saito, Kazuma Iteya, Masaya Nomura, Takayuki Nakamura

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

2014

Information-Maximization Clustering Based on Squared-Loss Mutual Information.

Masashi Sugiyama, Gang Niu, Makoto Yamada, Manabu Kimura, Hirotaka Hachiya

Neural Comput., 2014

2013

Efficient Sample Reuse in Policy Gradients with Parameter-Based Exploration.

Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt, Jun Morimoto, Masashi Sugiyama

Neural Comput., 2013

Relative Density-Ratio Estimation for Robust Distribution Comparison.

Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Masashi Sugiyama

Neural Comput., 2013

Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting.

Ning Xie, Hirotaka Hachiya, Masashi Sugiyama

IEICE Trans. Inf. Syst., 2013

Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifiers.

Hyun Ha Nam, Hirotaka Hachiya, Masashi Sugiyama

IEICE Trans. Inf. Syst., 2013

Feature Selection via l₁-Penalized Squared-Loss Mutual Information.

Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama

IEICE Trans. Inf. Syst., 2013

Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning.

Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama

Proceedings of the 30th International Conference on Machine Learning, 2013

NSH: Normality Sensitive Hashing for Anomaly Detection.

Hirotaka Hachiya, Masakazu Matsugu

Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013

2012

Analysis and improvement of policy gradient estimation.

Tingting Zhao, Hirotaka Hachiya, Gang Niu, Masashi Sugiyama

Neural Networks, 2012

Importance-weighted least-squares probabilistic classifier for covariate shift adaptation with application to human activity recognition.

Hirotaka Hachiya, Masashi Sugiyama, Naonori Ueda

Neurocomputing, 2012

Multi-Task Approach to Reinforcement Learning for Factored-State Markov Decision Problems.

Jaak Simm, Masashi Sugiyama, Hirotaka Hachiya

IEICE Trans. Inf. Syst., 2012

Feature Selection via L1-Penalized Squared-Loss Mutual Information

Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama

CoRR, 2012

Computationally efficient multi-label classification by least-squares probabilistic classifier.

Hyun Ha Nam, Hirotaka Hachiya, Masashi Sugiyama

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning.

Hirotaka Hachiya, Jan Peters, Masashi Sugiyama

Neural Comput., 2011

On Information-Maximization Clustering: Tuning Parameter Selection and Analytic Solution.

Masashi Sugiyama, Makoto Yamada, Manabu Kimura, Hirotaka Hachiya

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Efficient exploration through active learning for value function approximation in reinforcement learning.

Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiyama

Neural Networks, 2010

Conditional Density Estimation via Least-Squares Density Ratio Estimation.

Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Daisuke Okanohara

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Least-Squares Conditional Density Estimation.

Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Daisuke Okanohara

IEICE Trans. Inf. Syst., 2010

Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation.

Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura

IEICE Trans. Inf. Syst., 2010

Parametric Return Density Estimation for Reinforcement Learning.

Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka

Proceedings of the UAI 2010, 2010

Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information.

Hirotaka Hachiya, Masashi Sugiyama

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Nonparametric Return Distribution Approximation for Reinforcement Learning.

Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Adaptive importance sampling for value function approximation in off-policy reinforcement learning.

Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters

Neural Networks, 2009

Efficient Sample Reuse in EM-Based Policy Search.

Hirotaka Hachiya, Jan Peters, Masashi Sugiyama

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Active Policy Iteration: Efficient Exploration through Active Learning for Value Function Approximation in Reinforcement Learning.

Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiyama

Proceedings of the IJCAI 2009, 2009

Least absolute policy iteration for robust value function approximation.

Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura

Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009

Efficient data reuse in value function approximation.

Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters

Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

2008

Geodesic Gaussian kernels for value function approximation.

Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell, Sethu Vijayakumar

Auton. Robots, 2008

Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation.

Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

Value Function Approximation on Non-Linear Manifolds for Robot Motor Control.

Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell, Sethu Vijayakumar

Proceedings of the 2007 IEEE International Conference on Robotics and Automation, 2007