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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE (Joint) |
2024-03-11 16:50 |
Tokyo | The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
A Method of Timbre Synthesis Reflecting Impression Using Conditional-VAE
-- Applying the Temporal Information -- Miyu Yoshikawa, Susumu Kuroyanagi (NIT)  NC2023-49 |
It is difficult to systematically explain the relationship between tones and the impressions people have of them. In th... [more] | NC2023-49 pp.37-42 |
| IBISML | 2023-12-20 16:25 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Anomaly detection by deep support data descriptions with pseudo-anomaly data Shuta Tsuchio, Takuya Kitamura (NIT, Toyama college) IBISML2023-34 |
This paper presents deep support vector data description (DSVDD) with pseudo-anomaly data that generated by generative m... [more] | IBISML2023-34 pp.25-30 |
| PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI | 2023-11-17 09:20 |
Tottori | (Primary: On-site, Secondary: Online) |
Co-speech Gesture Generation with Variational Auto Encoder Shihichi Ka, Koichi Shinoda (Tokyo Tech) PRMU2023-29 |
Co-speech gesture generation is the study of generating gestures from speech. In prior works, deterministic methods lear... [more] | PRMU2023-29 pp.74-79 |
| AI | 2023-09-12 15:35 |
Hokkaido | Variational Autoencoder Oriented Protection for Intellectual Property Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) AI2023-31 |
In recent years, generative AI, which generates images based on instructions in natural language, has developed rapidly ... [more] | AI2023-31 pp.180-186 |
|
| MSS, CAS, SIP, VLD | 2023-07-06 14:40 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Convergence Acceleration of Particle-based Variational Inference by Deep Unfolding Yuya Kawamura, Satoshi Takabe (Tokyo Tech) CAS2023-8 VLD2023-8 SIP2023-24 MSS2023-8 |
Stein Variational Gradient Descent(SVGD) is a prominent particle-based variational inference method used for estimating ... [more] | CAS2023-8 VLD2023-8 SIP2023-24 MSS2023-8 pp.37-42 |
| QIT (2nd) |
2023-05-29 16:30 |
Kyoto | Katsura Campus, Kyoto University | [Poster Presentation]
Quantum Circuit Synthesis Method of VQE for Traveling Salesman Problem Considering W States Kohei Ogino (Ritsumeikan Univ.), Atsushi Matsuo (IBM Japan), Shigeru Yamashita (Ritsumeikan Univ.) |
VQE (Variational Quantum Eigensolver), a quantum algorithm, can be used to solve combinatorial optimization problems usi... [more] | |
| RCC, ISEC, IT, WBS | 2023-03-14 15:45 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Improvement of the Performance for Quantum Neural Network Classifiers based on Optimal Quantum Measurement Decoding Yusaku Yamada, Jun Suzuki (UEC) IT2022-106 ISEC2022-85 WBS2022-103 RCC2022-103 |
In this work, we study the problem of supervised label classification using quantum neural network (QNN). We propose a m... [more] | IT2022-106 ISEC2022-85 WBS2022-103 RCC2022-103 pp.242-247 |
| NC, MBE (Joint) |
2023-03-14 15:25 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
A Method of Timbre Synthesis Reflecting Impression Using Conditional-VAE
-- Conditioning by Impression and Generating Sound Waveforms -- Takeru Watanabe, Susumu Kuroyanagi (NIT) NC2022-106 |
In This paper, we aim to propose a method of timbre synthesis based on impressions recalled by humans. We worked on this... [more] | NC2022-106 pp.84-89 |
| IT, RCS, SIP | 2023-01-25 14:35 |
Gunma | Maebashi Terrsa (Primary: On-site, Secondary: Online) |
An Optimal Prediction on Multilevel Coefficient Linear Regression Model by Bayes Decision Theory and Its Approximation Method Kohei Horinouchi, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.) IT2022-67 SIP2022-118 RCS2022-246 |
It is common practice to apply Multilevel Analysis for the data sampled from various classes. In this Analysis, it is co... [more] | IT2022-67 SIP2022-118 RCS2022-246 pp.217-222 |
| QIT (2nd) |
2022-12-08 17:45 |
Kanagawa | Keio Univ. (Primary: On-site, Secondary: Online) |
Optimal Measurement Configurations for Sequential Quantum Optimization of Variational Quantum Eigensolver Katsuhiro Endo (AIST/Keio Univ.), Hiroshi Watanabe (Keio Univ.), Yuki Sato (Toyota Central R&D Labs., Inc./Keio Univ.), Rudy Raymond (IBM Japan,Ltd./Keio Univ./The Univ. of Tokyo), Naoki Yamamoto, Mayu Muramatsu (Keio Univ.) |
Variational Quantum Eigenvalue solver (VQE) is a hybrid algorithm that optimizes a quantum state represented by a parame... [more] | |
| SIP | 2022-08-25 13:21 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Style Feature Extraction by Contrastive Learning and Mutual Information Constraints Suguru Yasutomi, Toshihisa Tanaka (TUAT) SIP2022-52 |
Extracting style features is crucial for analyzing data. This paper proposes a style feature extraction using variationa... [more] | SIP2022-52 pp.13-18 |
| SIP | 2022-08-26 14:08 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Study on Bone-conducted Speech Enhancement Using Vector-quantized Variational Autoencoder and Gammachirp Filterbank Cepstral Coefficients Quoc-Huy Nguyen, Masashi Unoki (JAIST) SIP2022-71 |
Bone-conducted (BC) speech potentially avoids the undesired effects on recorded speech due to background noise or reverb... [more] | SIP2022-71 pp.109-114 |
| RCS | 2022-06-16 14:30 |
Okinawa | University of the Ryukyus, Senbaru Campus and online (Primary: On-site, Secondary: Online) |
Comparison of Performance and Complexity for different Search Methods in Stochastic MIMO Signal Detection Hiroki Asumi, Yukiko Kasuga, Kazushi Matsumura, Junichiro Hagiwara, Toshihiko Nishimura, Takanori Sato, Yasutaka Ogawa, Takeo Ohgane (Hokkaido Univ.) RCS2022-49 |
In large-scale MIMO signal detection, the computational complexity increases as the number of antennas increases. We hav... [more] | RCS2022-49 pp.150-155 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-19 09:40 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Variational Autoencoders Conditioned by Contrastive Features as Style-Feature Extractors Suguru Yasutomi, Toshihisa Tanaka (TUAT) SIP2022-3 BioX2022-3 IE2022-3 MI2022-3 |
Extracting style features is crucial for investigating the characteristics of data. This paper proposes a variational au... [more] | SIP2022-3 BioX2022-3 IE2022-3 MI2022-3 pp.13-18 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-01 14:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Target speaker extraction based on conditional variational autoencoder and directional information in underdetermined condition Rui Wang, Li Li, Tomoki Toda (Nagoya Univ) EA2021-76 SIP2021-103 SP2021-61 |
This paper deals with a dual-channel target speaker extraction problem in underdetermined conditions. A blind source sep... [more] | EA2021-76 SIP2021-103 SP2021-61 pp.76-81 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 16:45 |
Online | Online | A Note on Disentanglement Using Deep Generative Model Based on Variational Autoencoder
-- Introduction of Regularization Losses Based on Metrics of Disentangled Representation -- Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study disentangled representation learning using a deep generative model based on Variational Autoenco... [more] | |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 10:55 |
Online | Online | Reward-oriented Environment Inference on Reinforcement Learning Kazuki Takahashi (Kogakuin Univ.), Tomoki Fukai (OIST), Yutaka Sakai (Tamagawa Univ.), Takashi Takekawa (Kogakuin Univ.) NC2021-42 |
Experiments on humans using the bandit problem have shown that dimensionality reduction of complex observations to a sta... [more] | NC2021-42 pp.49-54 |
| PRMU | 2021-12-16 16:45 |
Online | Online | Verification of Cyclical Annealing for Object-Oriented Representation Learning Atsushi Kobayashi (Waseda Univ.), Hideki Tsunashima (Waseda Univ./AIST), Takehiko Ohkawa (The Univ. of Tokyo), Hiroaki Aizawa (Hiroshima Univ.), Qiu Yue, Hirokatsu Kataoka (AIST), Shigeo Morishima (Waseda Univ.) PRMU2021-39 |
Object-oriented Representation Learning is a method for obtaining images for each object and background part from an ima... [more] | PRMU2021-39 pp.83-87 |
| IT | 2021-07-09 13:00 |
Online | Online | Bayesian Optimal Prediction and Its Approximation Algorithm for the Difference of Response Variables with and without Measures Considering Individual Differences by Assuming Latent Clusters Taisuke Ishiwatari (Waseda Univ.), Shota Saito (Gunma Univ.), Toshiyasu Matsushima (Waseda Univ.) IT2021-23 |
In observational studies, there are problems such as "the measure can be given only once to the target" and "the charact... [more] | IT2021-23 pp.45-50 |
| IT | 2021-07-09 13:25 |
Online | Online | A Note on the Reduction of Computational Complexity for Linear Regression Model Including Cluster Explanatory Variables and Regression Explanatory Variables
-- Bayes Optimal Prediction and Sub-Optimal Algorithm -- Sho Kayama (Waseda Univ.), Shota Saito (Gunma Univ.), Toshiyasu Matsushima (Waseda Univ.) IT2021-24 |
By considering the probability model with the structure that the data is divided into clusters and each cluster has an i... [more] | IT2021-24 pp.51-56 |
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