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幾何学、力学系、トポロジー メーリングリストの皆様<br>
クロスポストをご容赦ください。<br>
<br>
武蔵野大学数理工学センターでは，次のように第57回MCMEセミナー、第58回MCMEセミナー<br>
<a class="moz-txt-link-freetext" href="https://www.musashino-u.ac.jp/research/laboratory/mathematical_engineering/seminar_symposium.html">https://www.musashino-u.ac.jp/research/laboratory/mathematical_engineering/seminar_symposium.html</a><br>
を開催いたします．<br>
参加をご希望の方は，ウェブページ内の「参加申し込みフォーム」より第57回は6月19日（月）、<br>
第58回は 7/3（月） までに参加登録をお願いいたします．（第58回は私からは以前に第57回としてお知らせしたものです）<br>
皆様のご参加をお待ちしております．<br>
武蔵野大学数理工学センター<br>
坪井 俊<br>
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!important; float: none;">====== 第57回MCMEセミナー ハイブリッド開催のご案内 ======</span><br
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<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
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!important; float: none;">開催日時：2023年6月21日(水)17：00〜18：30</span><br
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<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
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!important; float: none;">開催地 ：武蔵野大学有明キャンパス 4号館412教室</span><br
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<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
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!important; float: none;">参加登録URL：</span><a
href="https://forms.gle/YzQTKjgwRBbF8mqAA" rel="noreferrer"
target="_blank"
data-saferedirecturl="https://www.google.com/url?q=https://forms.gle/YzQTKjgwRBbF8mqAA&source=gmail&ust=1685583950015000&usg=AOvVaw14MHVg3X9q5lmEF7c-lsR2"
style="font-family: "Google Sans", Roboto, RobotoDraft,
Helvetica, Arial, sans-serif; background-color: rgb(255, 255,
255); color: rgb(17, 85, 204); font-size: small; font-style:
normal; font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px;">https://forms.gle/YzQT<wbr style="font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial, sans-serif;">KjgwRBbF8mqAA</a><br
style="font-family: "Google Sans", Roboto, RobotoDraft,
Helvetica, Arial, sans-serif; color: rgb(34, 34, 34); font-size:
small; font-style: normal; font-variant-ligatures: normal;
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initial; text-decoration-style: initial; text-decoration-color:
initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
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0px; background-color: rgb(255, 255, 255);
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!important; float: none;">参加登録締切：6月19日</span><br
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Helvetica, Arial, sans-serif; color: rgb(34, 34, 34); font-size:
small; font-style: normal; font-variant-ligatures: normal;
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initial; text-decoration-style: initial; text-decoration-color:
initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
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0px; background-color: rgb(255, 255, 255);
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!important; float: none;">講演者：唐木田 亮 氏（産業技術総合研究所 人工知能研究センター)</span><br
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small; font-style: normal; font-variant-ligatures: normal;
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background-color: rgb(255, 255, 255); text-decoration-thickness:
initial; text-decoration-style: initial; text-decoration-color:
initial;">
<br style="font-family: "Google Sans", Roboto,
RobotoDraft, Helvetica, Arial, sans-serif; color: rgb(34, 34, 34);
font-size: small; font-style: normal; font-variant-ligatures:
normal; font-variant-caps: normal; font-weight: 400;
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<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
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!important; float: none;">タイトル：深層学習アルゴリズムを操る: Fisher情報行列と学習レジーム</span><br
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Helvetica, Arial, sans-serif; color: rgb(34, 34, 34); font-size:
small; font-style: normal; font-variant-ligatures: normal;
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initial; text-decoration-style: initial; text-decoration-color:
initial;">
<br style="font-family: "Google Sans", Roboto,
RobotoDraft, Helvetica, Arial, sans-serif; color: rgb(34, 34, 34);
font-size: small; font-style: normal; font-variant-ligatures:
normal; font-variant-caps: normal; font-weight: 400;
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<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
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font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
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0px; background-color: rgb(255, 255, 255);
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!important; float: none;">アブストラクト：大規模な深層ニューラルネットは様々な課題で高</span><span
style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">い性能を発揮しているが, その学習手法には</span><br
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Helvetica, Arial, sans-serif; color: rgb(34, 34, 34); font-size:
small; font-style: normal; font-variant-ligatures: normal;
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normal; orphans: 2; text-align: start; text-indent: 0px;
text-transform: none; white-space: normal; widows: 2;
word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255); text-decoration-thickness:
initial; text-decoration-style: initial; text-decoration-color:
initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
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initial; text-decoration-color: initial; display: inline
!important; float: none;">発見的側面が強いものも多く, 未知の挙動も現れる.特に,
アルゴリズムは無数にある解の中から陰的に解を選択</span><br style="font-family:
"Google Sans", Roboto, RobotoDraft, Helvetica, Arial,
sans-serif; color: rgb(34, 34, 34); font-size: small; font-style:
normal; font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
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0px; background-color: rgb(255, 255, 255);
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initial; text-decoration-color: initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">するため, こうした陰的バイアスをふまえた理解が重要となってくる.
本講演では,深層学習アルゴリズムのふる</span><br style="font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial, sans-serif;
color: rgb(34, 34, 34); font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
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0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
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!important; float: none;">まいをFisher情報行列と学習レジームの視点から紹介したい</span><span
style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">. まず, 基本的な考え方を概観しながら,具体例とし</span><br
style="font-family: "Google Sans", Roboto, RobotoDraft,
Helvetica, Arial, sans-serif; color: rgb(34, 34, 34); font-size:
small; font-style: normal; font-variant-ligatures: normal;
font-variant-caps: normal; font-weight: 400; letter-spacing:
normal; orphans: 2; text-align: start; text-indent: 0px;
text-transform: none; white-space: normal; widows: 2;
word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255); text-decoration-thickness:
initial; text-decoration-style: initial; text-decoration-color:
initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">てNeural Tangent Kernel (NTK)
レジームにおける自然勾配法の解析を紹介する. ここでは,発見的に開発され</span><br style="font-family:
"Google Sans", Roboto, RobotoDraft, Helvetica, Arial,
sans-serif; color: rgb(34, 34, 34); font-size: small; font-style:
normal; font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">てきた近似自然勾配が最良の収束性を達成できる. また関連して,
勾配正則化とその線形ネットでの解析を紹介</span><br style="font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial, sans-serif;
color: rgb(34, 34, 34); font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial;">
<span style="color: rgb(34, 34, 34); font-family: Arial, Helvetica,
sans-serif; font-size: small; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2; text-align:
start; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width:
0px; background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">する.解の選択を学習レジームの切り替わりから特徴づける中で,
望ましいアルゴリズムの設定を明らかにする.</span><br style="font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial, sans-serif;
color: rgb(34, 34, 34); font-size: small; font-style: normal;
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<br style="font-family: "Google Sans", Roboto,
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!important; float: none;">主催：武蔵野大学 数理工学センター（MCME）<br>
==============================</span><span style="color: rgb(34,
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<br>
====== 第58回MCMEセミナー ハイブリッド開催のご案内 ======<br>
<br>
開催日時：2023年7月5日(水)17：00〜18：30<br>
開催地 ：武蔵野大学有明キャンパス ４号館４１２教室,ハイブリッド開催<br>
参加登録URL：<a class="moz-txt-link-freetext" href="https://forms.gle/YP4as6cLJUXB84cY6">https://forms.gle/YP4as6cLJUXB84cY6</a><br>
参加登録締切： 7月3日<br>
講演者：木村 芳文 氏（名古屋大学大学院多元数理科学研究科)<br>
<br>
タイトル：渦運動と流体方程式の特異性ートポロジカル流体力学の展開<br>
<br>
アブストラクト：流体運動の基礎方程式であるNavier-Stokes 方程式やその非粘性極限であるEuler
方程式は非線形の偏微分方程式ですが，その非線形項は簡単な変換で速度ベクトルと渦度ベクトルの
ベクトル積で表すことができます．よって空間内の速度と渦度の幾何学的な位置関係によって流体方
程式の非線形性が決まることが分かります。本講演ではクレイ数学研究所のミレニアム問題の一つで
ある「Navier-Stokes方程式の適切性/特異性」に関連して渦衝突/リコネクションに伴う特異性につ
いて最近の結果を理論と数値解析の両面からご紹介します。渦の相互作用によって誘起される速度場
が渦を引き延ばして強めていく過程を粘性がどのように阻害するかが問題のキーポイントです。 <br>
<br>
主催：武蔵野大学 数理工学センター（MCME）<br>
<br>
===<br>
<br>
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