Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SS, MSS |
2024-01-17 14:55 |
Ishikawa |
(Primary: On-site, Secondary: Online) |
Combined Constraint on Behavior Cloning and Discriminator in Offline Reinforcement Learning Shunya Kidera, Kosuke Shintani, Toi Tsuneda, Satoshi Yamane (Kanazawa Univ.) MSS2023-56 SS2023-35 |
[more] |
MSS2023-56 SS2023-35 pp.25-30 |
SS, MSS |
2024-01-18 11:30 |
Ishikawa |
(Primary: On-site, Secondary: Online) |
Deep Reinforcement Learning Using LMM's Studying Papers and Intrinsic Rewards Sota Nagano, Satoshi Yamane (Kanazawa Univ.) MSS2023-64 SS2023-43 |
Research combining deep reinforcement learning with a large language model (LLM) produced high scores even for open-worl... [more] |
MSS2023-64 SS2023-43 pp.70-75 |
MSS, SS |
2023-01-10 11:00 |
Osaka |
(Primary: On-site, Secondary: Online) |
[Panel Discussion]
Review of Mathematical Systems Science and its Applications (MSS) Research Group Activities and Future Prospects
-- Messages from Past MSS Chairs -- Atsuo Ozaki (OIT), Kunihiko Hiraishi (JAIST), Yuichi Nakamura (NEC), Satoshi Yamane (Kanazawa Univ.), Morikazu Nakamura (Univ. of the Ryukyus), Shigemasa Takai (Osaka Univ.) MSS2022-44 SS2022-29 |
Ten years have passed since the Mathematical Systems Science and its Applications (MSS) was established in 2011. To comm... [more] |
MSS2022-44 SS2022-29 pp.1-4 |
CAS, SIP, MSS, VLD |
2018-06-15 12:25 |
Hokkaido |
Hokkaido Univ. (Frontier Research in Applied Sciences Build.) |
[Panel Discussion]
The role of System and Signal Processing Subsociety
-- The roadmaps of groups and subsociety Part 1 -- Satoshi Yamane (Kanazawa Univ.), Hideaki Okazaki (Shonan Inst. of Tech.), Noriyuki Minegishi (Mitsubishi Electric), Shogo Muramatsu (Niigata Univ.), Morikazu Nakamura (Univ. of the Ryukyus) CAS2018-25 VLD2018-28 SIP2018-45 MSS2018-25 |
The four technical committees CAS, VLD, SIP, and MSS of System and Signal Processing Subsociety holds joint workshop sin... [more] |
CAS2018-25 VLD2018-28 SIP2018-45 MSS2018-25 p.129 |
MSS, NLP (Joint) |
2018-03-13 14:55 |
Osaka |
|
Deductive Verification of real-time safety properties for embedded assembly program using theorem prover Princess Naoki Odajima (Kanazawa Univ.), Gakuhi Fukuda (Kanazawa Nishikigaoka), Satoshi Yamane (Kanazawa Univ.) MSS2017-84 |
It is important to verify both the correctness and real-time properties for embedded systems.
In this paper, we propos... [more] |
MSS2017-84 pp.35-40 |
IBISML |
2017-11-10 13:00 |
Tokyo |
Univ. of Tokyo |
Rotated Image Recognition by Continuous execution of Angle Estimation Using a Feature Map with CNN Nishiki Katayama, Satoshi Yamane (Kanazawa Univ.) IBISML2017-63 |
Feature extraction by using a Convolutional Neural Network (CNN) has made remarkable results in general object recogniti... [more] |
IBISML2017-63 pp.215-218 |
SIP, CAS, MSS, VLD |
2017-06-20 09:30 |
Niigata |
Niigata University, Ikarashi Campus |
Deductive Verification Method of real-time safety properties for embedded assembly program
-- □≦TIME q = □(q∧(time≦TIME)) -- Satoshi Yamane (Kanazawa Univ.) CAS2017-12 VLD2017-15 SIP2017-36 MSS2017-12 |
It is important to verify both the correctness and real-time properties for embedded systems.
In this paper, we propos... [more] |
CAS2017-12 VLD2017-15 SIP2017-36 MSS2017-12 pp.59-64 |
MSS |
2017-03-16 11:20 |
Shimane |
Shimane Univ. |
Verification Methods of real-time properties for embedded assembly program
-- Model checking and deductive verification for embedded program -- Satoshi Yamane (Kanazawa Univ.) MSS2016-83 |
It is important to verify both the correctness and real-time properties for embedded systems.
In this paper, we propos... [more] |
MSS2016-83 pp.11-16 |
IBISML |
2016-11-16 15:00 |
Kyoto |
Kyoto Univ. |
A generation model of representations of sentence by convolution neural network for machine translation Shin Chadani, Satoshi Yamane, Kouhei Sakurai (Kanazawa Univ.) IBISML2016-52 |
In the task of machine translation, the word order of the language for translation is one of the important elements. Eng... [more] |
IBISML2016-52 pp.51-54 |
IBISML |
2016-11-16 15:00 |
Kyoto |
Kyoto Univ. |
Online heterogeneous mixture machine learning Tetsuya Ikehara, Satoshi Yamane (Kanazawa Univ.) IBISML2016-54 |
In recent years, utilization of big data has attracted the attention, and many techniques about data analysis have been ... [more] |
IBISML2016-54 pp.59-64 |
VLD, CAS, MSS, SIP |
2016-06-16 13:20 |
Aomori |
Hirosaki Shiritsu Kanko-kan |
[Panel Discussion]
The Role of System and Signal Processing Subsociety
-- Encouragement and Development of Young Researchers -- Yoshinobu Kajikawa (Kansai Univ.), Shunsuke Koshita (Tohoku Univ.), Takashi Takenaka (NEC), Yuichi Tanaka (TUAT), Satoshi Yamane (Kanazawa Univ.) CAS2016-9 VLD2016-15 SIP2016-43 MSS2016-9 |
The four technical committees of System and Signal Processing Subsociety have been holding joint workshop since 2010. We... [more] |
CAS2016-9 VLD2016-15 SIP2016-43 MSS2016-9 p.47 |
SS, MSS |
2016-01-25 11:45 |
Ishikawa |
Shiinoki-Geihin-Kan |
Application of Transition Predicate Abstraction to Non-Zeno Fairness Verification for Linear Hybrid Automaton Ryo Yanase, Satoshi Yamane (Kanazawa Univ.) MSS2015-40 SS2015-49 |
For verifying fairness properties of a hybrid system, in generally, it is necessary to show that the system also satisfi... [more] |
MSS2015-40 SS2015-49 pp.29-33 |
SS, MSS |
2016-01-26 13:20 |
Ishikawa |
Shiinoki-Geihin-Kan |
Implementation of Parallel Distributed Graph Clustering Algorithm on Apache Spark with Node Partition and Aggregation in Large-Scale Graphs Riku Asayama, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2015-60 SS2015-69 |
In this paper, we propose the rapid clustering method with the large-scaled graph structured data. Our approach is a dat... [more] |
MSS2015-60 SS2015-69 pp.141-146 |
MSS, CAS, IPSJ-AL [detail] |
2015-11-20 14:20 |
Kagoshima |
Ibusuki CityHall |
Program syntesis from execution traces andt its program verification of distributed algorithms Satoshi Yamane (Kanazawa Univ.) CAS2015-50 MSS2015-24 |
Distributed algorithms are executed on distributed systems such as cloud computing and P2P.
It is important to verify ... [more] |
CAS2015-50 MSS2015-24 pp.35-40 |
MSS, CAS, SIP, VLD |
2015-06-18 10:10 |
Hokkaido |
Otaru University of Commerce |
Software model checking of embedded assembly programs by symbolic execution Ryosuke Konoshita, Satoshi Yamane (Kanazawa Univ.) CAS2015-15 VLD2015-22 SIP2015-46 MSS2015-15 |
We have developed a software verification system for embedded assembly programs.
It dynamically generates a model by th... [more] |
CAS2015-15 VLD2015-22 SIP2015-46 MSS2015-15 pp.77-81 |
MSS |
2015-03-05 15:30 |
Ishikawa |
IT Business Plaza Musashi |
Code clone detection using parallel distributed processing for software revision history Shin Chadani, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2014-94 |
In software development with a version control system, code clones detected from the version history of the code can be ... [more] |
MSS2014-94 pp.19-24 |
MSS |
2015-03-05 16:05 |
Ishikawa |
IT Business Plaza Musashi |
Forcasting Individual stock prices using Deep Learning Kazuya Matsumoto, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2014-95 |
[more] |
MSS2014-95 pp.25-30 |
MSS |
2015-03-06 10:00 |
Ishikawa |
IT Business Plaza Musashi |
SMT-based Model Checking for Linear Hybrid Automata using CEGAR Shohei Tomisaka, Ryo Yanase, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2014-99 |
[more] |
MSS2014-99 pp.47-52 |
MSS |
2015-03-06 10:25 |
Ishikawa |
IT Business Plaza Musashi |
Development of SMT-based model checker for assembly cords using interrupts reduction technique Junpei Kobashi, Atsushi Takeshita, Satoshi Yamane, Kohei Sakurai (Kanazawa Univ.) MSS2014-100 |
Recently, embedded software has properties dependent on hardware (direct operation of address spaces, memory mapped I/O,... [more] |
MSS2014-100 pp.53-58 |
MSS |
2015-03-06 13:30 |
Ishikawa |
IT Business Plaza Musashi |
Parallel Distributed Clustering Algorithm with Node Partition and Aggregation in Large-Scale Graphs Riku Asayama, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2014-101 |
In this paper, we propose the rapid clustering method with the large-scaled graph structured data. Our approach is a dat... [more] |
MSS2014-101 pp.59-64 |