Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
QIT (2nd) |
2023-12-17 17:30 |
Okinawa |
OIST (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Optimal POVM with minimal size in two-parameter qubit-state estimation Jianchao Zhang, Jun Suzuki (UEC) |
In the realm of qubit state tomography, the accurate estimation of quantum states parameterized across the complete Bloc... [more] |
|
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] |
|
QIT (2nd) |
2022-12-08 14:00 |
Kanagawa |
Keio Univ. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
QestOptPOVM: Numerical search for finding an optimal POVM for multiparameter estimation Jianchao Zhang, Jun Suzuki (UEC) |
It is of fundamental question to find an optimal measurement (POVM) that extracts the most information available about t... [more] |
|
IT, EMM |
2022-05-18 13:30 |
Gifu |
Gifu University (Primary: On-site, Secondary: Online) |
Optimal measurement preserving map for quantum state estimation and hypothesis testing Jun Suzuki (UEC) IT2022-13 EMM2022-13 |
In this work we first introduce a notion of optimal decision preserving map for classical statistical decision theory, w... [more] |
IT2022-13 EMM2022-13 pp.67-72 |
CQ |
2019-08-27 09:50 |
Hokkaido |
Hakodate arena |
An Approximation of Average Latency for Constant Number Data Aggregation and Adaptive Control Based on Its Characteristics Hideaki Yoshino, Yuta Okuzawa, Ryunosuke Sugihara, Kenko Ota, Takefumi Hiraguri (NIT) CQ2019-58 |
To realize latency-critical IoT applications, latency should be minimized at IoT gateways that aggregate spatially distr... [more] |
CQ2019-58 pp.7-12 |
EMM |
2019-03-13 15:15 |
Okinawa |
TBD |
[Poster Presentation]
Estimation of Collusion Strategy for Fingerprinting Codes under Noisy Environment Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EMM2018-107 |
In fingerprinting code against collusion attack, the optimal detector which detect colluders has been proposed. However,... [more] |
EMM2018-107 pp.83-88 |
IBISML |
2019-03-06 11:30 |
Tokyo |
RIKEN AIP |
Optimal Kernel for Mode Estimation via Kernel Density Estimation Ryoya Yamasaki, Toshiyuki Tanaka (Kyoto Univ.) IBISML2018-113 |
We have derived kernel functions that minimize the asymptotic mean squared error of the mode estimate, which is defined ... [more] |
IBISML2018-113 pp.59-64 |
WBS, ITS, RCC |
2018-12-06 13:00 |
Okinawa |
Miyako Island Hirara Port Terminal Bldg. |
[Poster Presentation]
Belief Propagation Analysis for Synchronization over Sensor Network Ryosuke Adachi, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) WBS2018-52 ITS2018-35 RCC2018-83 |
In this paper, distributed estimation method with optimal aggregation based on belief propagation is proposed. In the se... [more] |
WBS2018-52 ITS2018-35 RCC2018-83 pp.135-139 |
CQ, ICM, NS, NV (Joint) |
2018-11-15 11:20 |
Ishikawa |
|
Characteristic Evaluation of Adaptive Control of Sensor Data Aggregation to Minimize Latency Hideaki Yoshino, Kenko Ota, Takefumi Hiraguri (NIT) CQ2018-68 |
In Internet of Things (IoT) systems utilizing a large amount of small-sized data, a data aggregation function, which hie... [more] |
CQ2018-68 pp.27-32 |
IEE-CMN, EMM, LOIS, IE, ITE-ME [detail] |
2018-09-28 13:15 |
Oita |
Beppu Int'l Convention Ctr. aka B-CON Plaza |
Dynamic Estimation of Collusion Strategy for the Detection of Colluders in Fingerprinting Codes Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Isao Echizen (NII) LOIS2018-19 IE2018-39 EMM2018-58 |
An optimal detector known as MAP detector has been proposed for the probabilistic fingerprinting
code. It needs two kin... [more] |
LOIS2018-19 IE2018-39 EMM2018-58 pp.65-70 |
R |
2018-05-25 15:30 |
Aichi |
Aichi Institute of Technology, Motoyama Campus |
Bayesian Interval Estimation of Optimal Software Release Time Based on a Discretized NHPP Model Shinji Inoue (Kansai Univ.), Shigeru Yamada (Tottori Univ.) R2018-4 |
We discuss an approach for obtaining interval estimation of optimal software release time which is derived by a discreti... [more] |
R2018-4 pp.19-24 |
EMM |
2018-03-05 14:35 |
Kagoshima |
Naze Community Center (Amami-Shi, Kagoshima) |
[Poster Presentation]
Estimation of Collusion Strategy for Fingerprinting Codes Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EMM2017-80 |
An optimal detector is known as MAP detector has been proposed for the probabilistic fingerprinting codes such as Tardo... [more] |
EMM2017-80 pp.17-22 |
QIT (2nd) |
2017-11-17 10:50 |
Saitama |
Saitama University |
Parameter Estimation of Quantum States from Optimal Design of Experiments Jun Suzuki (UEC) |
The problem of estimating parametric family of quantum states is analyzed based on the theory of optimal design of exper... [more] |
|
IBISML |
2016-11-17 14:00 |
Kyoto |
Kyoto Univ. |
Minimax optimal estimator for additively decomposable scalar functionals of discrete distributions Kazuto Fukuchi, Jun Sakuma (Univ. of Tsukuba) IBISML2016-82 |
We deal with a problem of estimating additively decomposable scalar functionals from a set of $n$ iid samples drawn from... [more] |
IBISML2016-82 pp.259-265 |
NLP |
2014-01-21 10:00 |
Hokkaido |
Niseko Park Hotel |
Mathematical structures of optimal solutions in continuous optimization problems (3)
-- Estimation of the number of isolated local minima and the number of connected components of local minimal values sets -- Hideo Kanemitsu (Hokkaido Univ. of Education) NLP2013-129 |
We show mathematical structures of optimal solutions in continuous optimization problem with continuous multivariate mul... [more] |
NLP2013-129 pp.1-6 |
SANE |
2013-12-03 09:50 |
Overseas |
VAST/VNSC(2nd Dec.) & Melia Hotel (3rd Dec), Hanoi, Vietnam |
TSUBAME Microsatellite: Design, Development and Verification of Attitude Determination and Control System Le Xuan Huy, Takashi Kamiya, Hao Ting, Shota Kawajiri (TITECH), Saburo Matsunaga (TITECH/JAXA) SANE2013-96 |
TSUBAME is the fourth satellite developed in the Laboratory for Space Systems (LSS) at Tokyo Institute of Technology and... [more] |
SANE2013-96 pp.145-150 |
NLP |
2013-10-28 15:00 |
Kagawa |
Sanport Hall Takamatsu |
Mathematical structure of optimal solutions in continuous optimization problems (2)
-- Necessary and sufficient optimality condition, and estimations of the number of solutions -- Hideo Kanemitsu (Hokkaido Univ. of Edu.), Hideyuki Imai (Hokkaido Univ.) NLP2013-81 |
We show mathematical structures of optimal solutions in continuous optimization problem with continuous multivariate mul... [more] |
NLP2013-81 pp.63-68 |
R |
2012-07-27 14:25 |
Hokkaido |
|
Confidence Interval Estimation of Optimal Checkpoint Interval Shunsuke Tokumoto, Tadashi Dohi (Hiroshima Univ,), Wong Young Yun (Pusan Nnational Univ.) R2012-16 |
Optimal checkpoint placement is a commonly used technique to generate the optimal checkpoint time sequence minimizing th... [more] |
R2012-16 pp.5-10 |
IBISML |
2011-06-21 14:15 |
Tokyo |
Takeda Hall |
Analysis and Improvement of Policy Gradient Estimation Tingting Zhao, Hirotaka Hachiya, Gang Niu, Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2011-12 |
Policy gradient is a useful model-free reinforcement learning approach,
but it tends to suffer from instability of grad... [more] |
IBISML2011-12 pp.83-89 |