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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NS, IN (Joint) |
2024-02-29 10:10 |
Okinawa | Okinawa Convention Center | Stochastic Geometry-based Transmission Power Analysis and Optimization for UAV Altitude in U2U in Inhomogeneous UAV Density Soma Shimizu, Takeshi Hirai, Naoki Wakamiya (Osaka Univ)  IN2023-73 |
This paper analyzes the impacts of inhomogeneous density distribution of unmanned aerial vehicles (UAVs) in UAV-to-UAV c... [more] | IN2023-73 pp.47-52 |
| NS, IN (Joint) |
2024-03-01 10:10 |
Okinawa | Okinawa Convention Center | On Game Theoretic Mining Task Offloading in Decentralized Applications Kota Yamada, Takanori Hara, Shoji Kasahara (NAIST) NS2023-198 |
With the increasing demand for blockchain-based Decentralized Applications (DApps), mining increas- ingly grows in impor... [more] | NS2023-198 pp.154-159 |
| SeMI | 2024-01-19 11:45 |
Yamanashi | Raki House Kaiji | Stochastic Geometry-based Transmission Power Optimization for UAV Altitude in U2U Communications Soma Shimizu, Takeshi Hirai, Naoki Wakamiya (Osaka Univ.) SeMI2023-69 |
This paper proposes a stochastic geometry-based analytical model and optimizes the transmission power per unmanned aeria... [more] | SeMI2023-69 pp.106-111 |
| IBISML | 2023-12-20 15:20 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Stabilization and Acceleration of Stochastic Gradient Descent Based on Eigenvalue Decomposition of the Fisher Information Matrix Masazumi Iida, Yoshinari Takeishi (Kyushu Univ.), Siyang Wang (Umea Univ.), Jun'ichi Takeuchi (Kyushu Univ.) IBISML2023-32 |
By using approximated eigen-decomposition of the Fisher information matrix, the Stabilizer method was recently developed... [more] | IBISML2023-32 pp.13-17 |
| RCC | 2021-01-22 13:55 |
Online | Online | Distributed Mini-Batch Stochastic Subgradient Algorithm over Directed Networks Daichi Ishikawa, Naoki Hayashi, Shigemasa Takai (Osaka Univ.) RCC2020-35 |
We consider a constrained optimization problem of minimizing the sum of the local convex objective function values of ag... [more] | RCC2020-35 pp.4-8 |
| MSS, CAS, IPSJ-AL [detail] | 2020-11-25 16:10 |
Online | Online | Distributed convex optimization with inequality constraints over directed graphs based on row stochasticity Hiroaki Sakuma, Naoki Hayashi, Shigemasa Takai (Osaka Univ.) CAS2020-22 MSS2020-14 |
Distributed optimization is a method in which agents exchange information on the network to obtain the optimal solution ... [more] | CAS2020-22 MSS2020-14 pp.16-21 |
| RCS | 2018-06-22 15:15 |
Nagasaki | Nagasaki University | Energy Efficiency Optimization in D2D-enabled Heterogeneous Cellular Networks Fereidoun H. Panahi (Keio Univ.), Farzad H. Panahi (UOK), Ghaith Hattab (UCLA), Tomoaki Ohtsuki (Keio Univ.), Danijela Cabric (UCLA) RCS2018-76 |
Small cells (SCs) offer a promising approach to meeting the exponentially growing data rate demands. However, dense depl... [more] | RCS2018-76 pp.243-248 |
| COMP | 2018-03-05 11:00 |
Osaka | Osaka Prefecture Univ. | [Invited Talk]
Stochastic Packing Integer Programs with Few Queries Takanori Maehara (RIKEN), Yutaro Yamaguchi (Osaka Univ./RIKEN) COMP2017-47 |
We consider a stochastic variant of the packing-type integer linear programming problem, which contains random variables... [more] | COMP2017-47 p.17 |
| ED | 2017-08-10 11:30 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Implementation Auto Parameter Optimization Mechanism in Robust Surface Myoelectric Detection Technique Using a Nonlinear Device Network Kazuki Inada, Yuki Inden, Seiya Kasai (Hokkaido Univ.) ED2017-35 |
Myoelectric signal (EMG) taken on the body surface of a user includes information of motion and position of the user act... [more] | ED2017-35 pp.53-56 |
| IBISML | 2017-03-07 10:30 |
Tokyo | Tokyo Institute of Technology | Doubly Accelerated Stochastic Variance Reduced Gradient Method for Regularized Empirical Risk Minimization Tomoya Murata, Taiji Suzuki (Tokyo Tech) IBISML2016-106 |
We develop a new stochastic gradient method for solving convex regularized empirical risk minimization problem in mini-b... [more] | IBISML2016-106 pp.49-56 |
| IBISML | 2017-03-07 11:30 |
Tokyo | Tokyo Institute of Technology | A stochastic optimization method and generalization bounds for voting classifiers by continuous density functions Atsushi Nitanda (Tokyo Tech./NTTDATA MSI), Taiji Suzuki (Tokyo Tech./JST/RIKEN) IBISML2016-108 |
We consider a learning method for the majority vote classifier by probability measure on continuously parametrized space... [more] | IBISML2016-108 pp.63-69 |
| CAS, ICTSSL | 2017-01-26 10:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Design of IIR Filters Changing Desired Frequency Response Kenzo Yamamoto, Kenji Suyama (Tokyo Denki Univ.) CAS2016-80 ICTSSL2016-34 |
In this paper, a design method for IIR (Infinite Impulse Response) filters is studied.A lot of local minimums exit in th... [more] | CAS2016-80 ICTSSL2016-34 pp.19-24 |
| IT, SIP, RCS | 2017-01-19 13:55 |
Osaka | Osaka City Univ. | Design of IIR Filters Adjusting A Parameter Depending on Specification Kenzo Yamamoto, Kenji Suyama (Tokyo Denki Univ.) IT2016-66 SIP2016-104 RCS2016-256 |
In this paper, a design method for IIR ( Infinite Impulse Response ) filters using PSO ( Particle Swarm Optimization ) i... [more] | IT2016-66 SIP2016-104 RCS2016-256 pp.117-122 |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | [Poster Presentation]
Stochastic Particle Gradient Descent for the Infinite Majority Vote Classifier Atsushi Nitanda, Taiji Suzuki (Tokyo Tech.) IBISML2016-79 |
We consider a learning method for the infinite majority vote classifier combined by a density on a continuous space of b... [more] | IBISML2016-79 pp.235-241 |
| VLD, CAS, MSS, SIP | 2016-06-17 12:00 |
Aomori | Hirosaki Shiritsu Kanko-kan | A Design Method of IIR Filters by Adjusting Design Specification Kenzo Yamamoto, Kenji Suyama (Tokyo Denki Univ.) CAS2016-25 VLD2016-31 SIP2016-59 MSS2016-25 |
In this paper, a design method for IIR (Infinite Impulse Response) filters using PSO (Particle Swarm Optimization) is st... [more] | CAS2016-25 VLD2016-31 SIP2016-59 MSS2016-25 pp.133-138 |
| CAS | 2016-01-28 11:25 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Design of IIR Filters Using PSO Adjusting An Additional Range of Penalty Function Kenzo Yamamoto, Kenji Suyama (Tokyo Denki Univ.) CAS2015-62 |
In this paper, a design method for IIR ( Infinite Impulse Response ) filters using PSO ( Particle Swarm Optimization ) i... [more] | CAS2015-62 pp.7-11 |
| MSS, CAS, IPSJ-AL [detail] | 2015-11-20 17:10 |
Kagoshima | Ibusuki CityHall | Design of IIR Filters Using PSO with Alternative Intensification and Diversification Kenzo Yamamoto, Yuji Nishimura, Kenji Suyama (Tokyo Denki Univ.) CAS2015-54 MSS2015-28 |
In this paper, a design method for IIR (Infinite Impulse Response) filters using PSO (Particle Swarm Optimization) is de... [more] | CAS2015-54 MSS2015-28 pp.71-76 |
| MSS, CAS, IPSJ-AL [detail] | 2015-11-20 17:35 |
Kagoshima | Ibusuki CityHall | Design of CSD Coefficient FIR Filters Using 0-1PSO with Successive Search Takahiro Danbara, Kiyotaka Kitahara, Kenji Suyama (Tokyo Denki Univ.) CAS2015-55 MSS2015-29 |
In this paper, a design of CSD (Canonic Signed Digit) coefficient FIR (Finite Impulse Response) filters using 0-1PSO hav... [more] | CAS2015-55 MSS2015-29 pp.77-82 |
| AI | 2015-06-18 14:55 |
Tokyo | A Study on Multiple Sampling and Cooperation Strategy for Stochastic Distributed Constraint Optimization Method Toshihiro Matsui (NITech) AI2015-7 |
Distributed Gibbs (DGibbs) is a sampling-based stochastic solution method for Distributed Constraint Optimization Proble... [more] | AI2015-7 pp.37-42 |
|
| NLP | 2015-04-24 13:55 |
Kagawa | Kagawa Social Welfare Center | High Sensitive Detecting Technique for Weak Signal by Stochastic Resonance Wen Li, Hisaaki Kanai, Kengo Imagawa, Masami Makuuchi, Hideki Osaka (Hitachi) NLP2015-21 |
Stochastic resonance (SR), a phenomenon that signals can be enhanced with especial noise strength in a non-linear system... [more] | NLP2015-21 pp.99-104 |
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