The era of genomic evaluation has brought the need to
perform computations involving large, dense matrices. Particular tasks are the computation and inversion of the genomic relationship matrix. This paper investigates the suitability of Graphics Processing Units together with highly optimised software libraries for these computations, using blocked algorithms. It is shown that calculations
are readily sped up by parallel processing, using freely available library routines, and that reductions in time by factors of 4 to 5 are achievable even for `consumer' grade graphics cards.
The era of genomic evaluation has brought the need to
perform computations involving large, dense matrices. Particular tasks are the computation and inversion of the genomic relationship matrix. This paper investigates the suitability of Graphics Processing Units together with highly optimised software libraries for these computations, using blocked algorithms. It is shown that calculations
are readily sped up by parallel processing, using freely available library routines, and that reductions in time by factors of 4 to 5 are achievable even for `consumer' grade graphics cards.
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Penalized maximum likelihood estimates of genetic covariance matrices wit...prettygully
A simulation study examining the effects of `regularization' on estimates of genetic covariance matrices for small samples is presented. This is achieved by penalizing the likelihood, and three types of penalties are examined. It is shown that regularized estimation can substantially enhance the accuracy of estimates of genetic parameters. Penalties shrinking estimates of genetic covariances or correlations towards their phenotypic counterparts acted somewhat differently to those aimed reducing the
spread of sample eigenvalues. While improvements of estimates were found to be comparable overall, shrinkage of genetic towards phenotypic correlations resulted in least bias.
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Penalized maximum likelihood estimates of genetic covariance matrices wit...prettygully
A simulation study examining the effects of `regularization' on estimates of genetic covariance matrices for small samples is presented. This is achieved by penalizing the likelihood, and three types of penalties are examined. It is shown that regularized estimation can substantially enhance the accuracy of estimates of genetic parameters. Penalties shrinking estimates of genetic covariances or correlations towards their phenotypic counterparts acted somewhat differently to those aimed reducing the
spread of sample eigenvalues. While improvements of estimates were found to be comparable overall, shrinkage of genetic towards phenotypic correlations resulted in least bias.
「4次元ポケットのないドラえもんのような存在を作りたい」というPO笠原の言葉から始まった Romi プロジェクト。会社のこれまでのプロジェクトには AI を主眼としたものもハードウェアを作るものもほとんど無い。そんな中にエンジニア一人飛び込んで会話 AI とロボットを作っていく。
企画的な価値も、それをどうすれば実現できるのかもわからない状態からアジャイルな考えに基づいて試行錯誤しながらユーザーに愛されるロボットができるまでのお話をさせていただきます。
A working hypothesis by H. Wagatsuma and D. Jahng (2020):
On-the-job training is apparently important to enhance learners' potential for learning capabilities. An actual problem is how the instructor well prepares stairs up to the next step, which finally reaches a goal. In this sense, a mission-oriented learning program & formative assessment is significantly helpful.
Public Hearing of Ph.D. Thesis of Jisha Maniamma /マニアマ ジーシャ 学位論文公聴会Hiroaki Wagatsuma
A Description Logic Architecture to Reconstitute the Minimal Semantic Representation Equivalent to the Unique Solution of Bongard's Ill-Posed Problems Considered to be Incapable Without Human Intuition.
(和訳):ボンガード不良設定問題の解導出と等価な最小論理集合を再構成する述語論理アーキテクチャに関する研究
This is the second orientation slide (in Japanese ) to explain hints and the method to spend a comfortable time in the lab to concentrate research activities when you will be a member of Wagatsuma Laboratory, Department of Human Intelligence Systems, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (KYUTECH)
This is the first orientation slide (in Japanese ) to explain rules and the policy in the lab when you will be a member of Wagatsuma Laboratory, Department of Human Intelligence Systems, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (KYUTECH)
Having your ambition, holding dreams and making endless
efforts to keep "to be what you wanted to be." To pursue
what you want to be, from the ambition and dream, even if
someone says "it is okay anymore". Continue to pursue it
until you are satisfied yourself.
2. 様々な非線形方程式、数理物理の基礎
Various non-linear equations
• 現代のロボット技術 (What it can do now)
• ロボットは人と暮らせるか? (What do you want)
• ロボットに求められるもの (What is necessary)
• ロボットはどうやって作るか (How you can build,
i.e. What kinds of strategies to achieve desired functions and
satisfy all the requirements)
in the viewpoint of making an intelligent robot to be
able to live with humans cooperatively
人間共生型ロボットの観点から
3. これを「自動車」に置き換えてみると ...
Try to think about CAR instead of the robot
• 自動車は何のためにあるか (What is the car for)
• 自動車は何ができるか (What it can do)
• 自動車に求められるもの (What is appropriate)
• 自動車に求められるもの (What we need)
• 自動車はどうやって走るのか (How it works)
- Usability, familiarity ( set the level that usual
people can get accustomed )
- 安全性と信頼性 (Safety and reliability; safe for others
and is not broken unexpectedly)
- メカニズムを知り、改善する (to know the
mechanism and improve it )
4. • ロボットは何のためにあるか (What for)
• ロボットは何ができるか (What it can do)
• ロボットに求められるもの (What is appropriate)
• ロボットに求められるもの (What we need)
• ロボットはどうやって賢くなるか (How it works
well)
- Knowing and understanding human beings ( for living
together comfortably )
- 安全性と信頼性 (Safety and reliability; safe for others and is
not broken unexpectedly)
- Investigate brain mechanisms such as intention,
emotion and feelings. Finally we reach a way of
implementation
すなわち、考えてみるべきことは ...
Thus, we have to think
5. ロボットの定義
• 認知・判断・理解などの人間(生物)が持つ能力
について、特定の目的のために、代替するもの
• A substitution of human abilities (recognition,
decision-making, understanding and so on) based
on a specific purpose
• →自動化 自律化
Automation and autonomous robot are different
( autonomous -> self discipline )
• personal memory, sympathy,
awareness are necessary?
The definition of robots
6. ロボットの定義
• 認知・判断・理解などの人間(生物)が持つ能力
について、特定の目的のために、代替するもの
• A substitution of human abilities (recognition,
decision-making, understanding and so on) based
on a specific purpose
• →自動化 自律化
Automation and autonomous robot are different
( autonomous -> self discipline )
• personal memory, sympathy,
awareness are necessary?
The definition of robots