Hideaki Kim

According to our database, Hideaki Kim authored at least 21 papers between 2009 and 2024.

Collaborative distances:

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

2024

A Continuous-time Tractable Model for Present-biased Agents.

Yasunori Akagi, Hideaki Kim, Takeshi Kurashima

CoRR, 2024

Meta-Learning for Neural Network-based Temporal Point Processes.

Yoshiaki Takimoto, Yusuke Tanaka, Tomoharu Iwata, Maya Okawa, Hideaki Kim, Hiroyuki Toda, Takeshi Kurashima

CoRR, 2024

Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions.

Hideaki Kim

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

MAP inference algorithms without approximation for collective graphical models on path graphs via discrete difference of convex algorithm.

Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda

Mach. Learn., January, 2023

Survival Permanental Processes for Survival Analysis with Time-Varying Covariates.

Hideaki Kim

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

An Improved Approximation Algorithm for Wage Determination and Online Task Allocation in Crowd-Sourcing.

Yuya Hikima, Yasunori Akagi, Hideaki Kim, Taichi Asami

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Fast Bayesian Estimation of Point Process Intensity as Function of Covariates.

Hideaki Kim, Taichi Asami, Hiroyuki Toda

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Matching with Controllable Rewards and Arrival Probabilities.

Yuya Hikima, Yasunori Akagi, Naoki Marumo, Hideaki Kim

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation.

Hideaki Kim

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm.

Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization.

Yuya Hikima, Yasunori Akagi, Hideaki Kim, Masahiro Kohjima, Takeshi Kurashima, Hiroyuki Toda

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2017

Analyzing Temporal Dynamics of Consumer's Behavior Based on Hierarchical Time-Rescaling.

Hideaki Kim, Noriko Takaya, Hiroshi Sawada

IEICE Trans. Inf. Syst., 2017

Scaling Locally Linear Embedding.

Yasuhiro Fujiwara, Naoki Marumo, Mathieu Blondel, Koh Takeuchi, Hideaki Kim, Tomoharu Iwata, Naonori Ueda

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

Online Traffic Flow Prediction Using Convolved Bilinear Poisson Regression.

Maya Okawa, Hideaki Kim, Hiroyuki Toda

Proceedings of the 18th IEEE International Conference on Mobile Data Management, 2017

SVD-Based Screening for the Graphical Lasso.

Yasuhiro Fujiwara, Naoki Marumo, Mathieu Blondel, Koh Takeuchi, Hideaki Kim, Tomoharu Iwata, Naonori Ueda

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Read the Silence: Well-Timed Recommendation via Admixture Marked Point Processes.

Hideaki Kim, Tomoharu Iwata, Yasuhiro Fujiwara, Naonori Ueda

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2014

Tracking Temporal Dynamics of Purchase Decisions via Hierarchical Time-Rescaling Model.

Hideaki Kim, Noriko Takaya, Hiroshi Sawada

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2013

Estimating inputs and an internal neuronal parameter from a single spike train.

Shigeru Shinomoto, Hideaki Kim

Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012

Neurons as ideal change-point detectors.

Hideaki Kim, Barry J. Richmond, Shigeru Shinomoto

J. Comput. Neurosci., 2012

2011

Elemental Spiking Neuron Model for Reproducing Diverse Firing Patterns and Predicting Precise Firing Times.

Satoshi Yamauchi, Hideaki Kim, Shigeru Shinomoto

Frontiers Comput. Neurosci., 2011

2009

Relating Neuronal Firing Patterns to Functional Differentiation of Cerebral Cortex.

Shigeru Shinomoto, Hideaki Kim, Takeaki Shimokawa, Nanae Matsuno, Shintaro Funahashi, Keisetsu Shima, Ichiro Fujita, Hiroshi Tamura, Taijiro Doi, Kenji Kawano, Naoko Inaba, Kikuro Fukushima, Sergei Kurkin, Kiyoshi Kurata, Masato Taira, Ken-Ichiro Tsutsui, Hidehiko Komatsu, Tadashi Ogawa, Kowa Koida, Jun Tanji, Keisuke Toyama

PLoS Comput. Biol., 2009