t r r s t t t s r t
play

t rrstt ts r - PowerPoint PPT Presentation

Nov 21, 2022 •209 likes •724 views

t rrstt ts r t rs r t rst st

  1. ❖♥ t❤❡ r❡♣r❡s❡♥t❛❜✐❧✐t② ♦❢ ❛❝t✐♦♥s ❢♦r t♦♣♦❧♦❣✐❝❛❧ ❣r♦✉♣s ❆♥❞r❡❛ ▼♦♥t♦❧✐ ❯♥✐✈❡rs✐tà ❞❡❣❧✐ st✉❞✐ ❞✐ ▼✐❧❛♥♦ ❏✉♥❡ ✶✼t❤ ✷✵✶✼ ❏♦✐♥t ✇♦r❦ ✇✐t❤ ❋r❛♥❝✐s ❇♦r❝❡✉① ❛♥❞ ▼❛r✐❛ ▼❛♥✉❡❧ ❈❧❡♠❡♥t✐♥♦

  2. ❢r♦♠ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ s ❳ ❆ ❇ ❢ ✇❡ ❣❡t ❛♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ❣✐✈❡♥ ❜② ✶ ❜ ① s ❜ ①s ❜ ❈♦♥✈❡rs❡❧②✱ ❢r♦♠ ❛♥ ❛❝t✐♦♥ ✇❡ ♦❜t❛✐♥ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ ✈✐❛ t❤❡ s❡♠✐❞✐r❡❝t ♣r♦❞✉❝t ❝♦♥str✉❝t✐♦♥✳ ●r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s ❚❤❡r❡ ✐s ❛ ✇❡❧❧✲❦♥♦✇♥ ❝♦rr❡s♣♦♥❞❡♥❝❡ ❜❡t✇❡❡♥ ❣r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✿

  3. ✶ ❜ ① s ❜ ①s ❜ ❈♦♥✈❡rs❡❧②✱ ❢r♦♠ ❛♥ ❛❝t✐♦♥ ✇❡ ♦❜t❛✐♥ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ ✈✐❛ t❤❡ s❡♠✐❞✐r❡❝t ♣r♦❞✉❝t ❝♦♥str✉❝t✐♦♥✳ � ●r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s ❚❤❡r❡ ✐s ❛ ✇❡❧❧✲❦♥♦✇♥ ❝♦rr❡s♣♦♥❞❡♥❝❡ ❜❡t✇❡❡♥ ❣r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✿ ❢r♦♠ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ s � ❆ � ❇ ❳ ❢ ✇❡ ❣❡t ❛♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ❣✐✈❡♥ ❜②

  4. ❈♦♥✈❡rs❡❧②✱ ❢r♦♠ ❛♥ ❛❝t✐♦♥ ✇❡ ♦❜t❛✐♥ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ ✈✐❛ t❤❡ s❡♠✐❞✐r❡❝t ♣r♦❞✉❝t ❝♦♥str✉❝t✐♦♥✳ � ●r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s ❚❤❡r❡ ✐s ❛ ✇❡❧❧✲❦♥♦✇♥ ❝♦rr❡s♣♦♥❞❡♥❝❡ ❜❡t✇❡❡♥ ❣r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✿ ❢r♦♠ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ s � ❆ � ❇ ❳ ❢ ✇❡ ❣❡t ❛♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ❣✐✈❡♥ ❜② ❜ · ① = s ( ❜ ) ①s ( ❜ ) − ✶ .

  5. � ●r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s ❚❤❡r❡ ✐s ❛ ✇❡❧❧✲❦♥♦✇♥ ❝♦rr❡s♣♦♥❞❡♥❝❡ ❜❡t✇❡❡♥ ❣r♦✉♣ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✿ ❢r♦♠ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ s � ❆ � ❇ ❳ ❢ ✇❡ ❣❡t ❛♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ❣✐✈❡♥ ❜② ❜ · ① = s ( ❜ ) ①s ( ❜ ) − ✶ . ❈♦♥✈❡rs❡❧②✱ ❢r♦♠ ❛♥ ❛❝t✐♦♥ ✇❡ ♦❜t❛✐♥ ❛ s♣❧✐t ❡①t❡♥s✐♦♥ ✈✐❛ t❤❡ s❡♠✐❞✐r❡❝t ♣r♦❞✉❝t ❝♦♥str✉❝t✐♦♥✳

  6. ❊q✉✐✈❛❧❡♥t❧②✱ ❛♥ ❛❝t✐♦♥ ✐s ❛ ❣r♦✉♣ ❤♦♠♦♠♦r♣❤✐s♠ ❇ ❆✉t ❳ ✳ ❱✐❛ t❤❡ ❡q✉✐✈❛❧❡♥❝❡ ❜❡t✇❡❡♥ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✱ t❤✐s ♠❡❛♥s t❤❛t t❤❡ ❢✉♥❝t♦r ❙♣❧❊①t ❳ ●♣ ❙❡t ✇❤✐❝❤ s❡♥❞s ❡✈❡r② ❣r♦✉♣ ❇ t♦ t❤❡ s❡t ❙♣❧❊①t ❇ ❳ ✱ ✐s r❡♣r❡s❡♥t❛❜❧❡✱ ✐✳❡✳ ✐t ✐s ♦❢ t❤❡ ❢♦r♠ ❍♦♠ ●♣ ❆✉t ❳ ✱ ✇❤❡r❡ ❆✉t✭❳✮ ✐s t❤❡ r❡♣r❡s❡♥t✐♥❣ ♦❜❥❡❝t✳ ❆❝t✐♦♥s ❛♥❞ ❛✉t♦♠♦r♣❤✐s♠s ❆♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ✐s ❛ ♠❛♣ ❇ × ❳ → ❳ s✉❝❤ t❤❛t ✶ ❜ · ( ① ✶ ① ✷ ) = ( ❜ · ① ✶ )( ❜ · ① ✷ ) ❀ ✷ ( ❜ ✶ ❜ ✷ ) · ① = ❜ ✶ · ( ❜ ✷ · ① ) ❀ ✸ ✶ · ① = ① ✳

  7. ❱✐❛ t❤❡ ❡q✉✐✈❛❧❡♥❝❡ ❜❡t✇❡❡♥ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✱ t❤✐s ♠❡❛♥s t❤❛t t❤❡ ❢✉♥❝t♦r ❙♣❧❊①t ❳ ●♣ ❙❡t ✇❤✐❝❤ s❡♥❞s ❡✈❡r② ❣r♦✉♣ ❇ t♦ t❤❡ s❡t ❙♣❧❊①t ❇ ❳ ✱ ✐s r❡♣r❡s❡♥t❛❜❧❡✱ ✐✳❡✳ ✐t ✐s ♦❢ t❤❡ ❢♦r♠ ❍♦♠ ●♣ ❆✉t ❳ ✱ ✇❤❡r❡ ❆✉t✭❳✮ ✐s t❤❡ r❡♣r❡s❡♥t✐♥❣ ♦❜❥❡❝t✳ ❆❝t✐♦♥s ❛♥❞ ❛✉t♦♠♦r♣❤✐s♠s ❆♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ✐s ❛ ♠❛♣ ❇ × ❳ → ❳ s✉❝❤ t❤❛t ✶ ❜ · ( ① ✶ ① ✷ ) = ( ❜ · ① ✶ )( ❜ · ① ✷ ) ❀ ✷ ( ❜ ✶ ❜ ✷ ) · ① = ❜ ✶ · ( ❜ ✷ · ① ) ❀ ✸ ✶ · ① = ① ✳ ❊q✉✐✈❛❧❡♥t❧②✱ ❛♥ ❛❝t✐♦♥ ✐s ❛ ❣r♦✉♣ ❤♦♠♦♠♦r♣❤✐s♠ ❇ → ❆✉t ( ❳ ) ✳

  8. ✐✳❡✳ ✐t ✐s ♦❢ t❤❡ ❢♦r♠ ❍♦♠ ●♣ ❆✉t ❳ ✱ ✇❤❡r❡ ❆✉t✭❳✮ ✐s t❤❡ r❡♣r❡s❡♥t✐♥❣ ♦❜❥❡❝t✳ ❆❝t✐♦♥s ❛♥❞ ❛✉t♦♠♦r♣❤✐s♠s ❆♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ✐s ❛ ♠❛♣ ❇ × ❳ → ❳ s✉❝❤ t❤❛t ✶ ❜ · ( ① ✶ ① ✷ ) = ( ❜ · ① ✶ )( ❜ · ① ✷ ) ❀ ✷ ( ❜ ✶ ❜ ✷ ) · ① = ❜ ✶ · ( ❜ ✷ · ① ) ❀ ✸ ✶ · ① = ① ✳ ❊q✉✐✈❛❧❡♥t❧②✱ ❛♥ ❛❝t✐♦♥ ✐s ❛ ❣r♦✉♣ ❤♦♠♦♠♦r♣❤✐s♠ ❇ → ❆✉t ( ❳ ) ✳ ❱✐❛ t❤❡ ❡q✉✐✈❛❧❡♥❝❡ ❜❡t✇❡❡♥ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✱ t❤✐s ♠❡❛♥s t❤❛t t❤❡ ❢✉♥❝t♦r ❙♣❧❊①t ( − , ❳ ): ●♣ → ❙❡t , ✇❤✐❝❤ s❡♥❞s ❡✈❡r② ❣r♦✉♣ ❇ t♦ t❤❡ s❡t ❙♣❧❊①t ( ❇ , ❳ ) ✱ ✐s r❡♣r❡s❡♥t❛❜❧❡✱

  9. ❆❝t✐♦♥s ❛♥❞ ❛✉t♦♠♦r♣❤✐s♠s ❆♥ ❛❝t✐♦♥ ♦❢ ❇ ♦♥ ❳ ✐s ❛ ♠❛♣ ❇ × ❳ → ❳ s✉❝❤ t❤❛t ✶ ❜ · ( ① ✶ ① ✷ ) = ( ❜ · ① ✶ )( ❜ · ① ✷ ) ❀ ✷ ( ❜ ✶ ❜ ✷ ) · ① = ❜ ✶ · ( ❜ ✷ · ① ) ❀ ✸ ✶ · ① = ① ✳ ❊q✉✐✈❛❧❡♥t❧②✱ ❛♥ ❛❝t✐♦♥ ✐s ❛ ❣r♦✉♣ ❤♦♠♦♠♦r♣❤✐s♠ ❇ → ❆✉t ( ❳ ) ✳ ❱✐❛ t❤❡ ❡q✉✐✈❛❧❡♥❝❡ ❜❡t✇❡❡♥ ❛❝t✐♦♥s ❛♥❞ s♣❧✐t ❡①t❡♥s✐♦♥s✱ t❤✐s ♠❡❛♥s t❤❛t t❤❡ ❢✉♥❝t♦r ❙♣❧❊①t ( − , ❳ ): ●♣ → ❙❡t , ✇❤✐❝❤ s❡♥❞s ❡✈❡r② ❣r♦✉♣ ❇ t♦ t❤❡ s❡t ❙♣❧❊①t ( ❇ , ❳ ) ✱ ✐s r❡♣r❡s❡♥t❛❜❧❡✱ ✐✳❡✳ ✐t ✐s ♦❢ t❤❡ ❢♦r♠ ❍♦♠ ●♣ ( − , ❆✉t ( ❳ )) ✱ ✇❤❡r❡ ❆✉t✭❳✮ ✐s t❤❡ r❡♣r❡s❡♥t✐♥❣ ♦❜❥❡❝t✳

  10. t♦ ❡✈❡r② ❡①t❡♥s✐♦♥ ❢ ❳ ❆ ❇ ❆✉t ❳ ✇❡ ❝❛♥ ❛ss♦❝✐❛t❡ ❛ ❤♦♠♦♠♦r♣❤✐s♠ ❇ ❖✉t ❳ ■♥♥ ❳ ✱ t❤❡ ❛❜str❛❝t ❦❡r♥❡❧ ♦❢ t❤❡ ❡①t❡♥s✐♦♥✳ ❚❤❡♦r❡♠ ✭❙❝❤r❡✐❡r✲▼❛❝ ▲❛♥❡✮ ❍ ✷ ❇ ❩ ❳ ❊①t ❇ ❳ ✇❤❡♥❡✈❡r ❊①t ❇ ❳ ✐s ♥♦t ❡♠♣t②✳ ❈♦♥s❡q✉❡♥❝❡s ♦❢ t❤❡ r❡♣r❡s❡♥t❛❜✐❧✐t② ♦❢ ❛❝t✐♦♥s ❚❤❡ r❡♣r❡s❡♥t❛❜✐❧✐t② ♦❢ ❛❝t✐♦♥s ❛❧❧♦✇s t❤❡ ❝❧❛ss✐✜❝❛t✐♦♥s ♦❢ ❡①t❡♥s✐♦♥s ✇✐t❤ ♥♦♥✲❛❜❡❧✐❛♥ ❦❡r♥❡❧✿

  11. ❚❤❡♦r❡♠ ✭❙❝❤r❡✐❡r✲▼❛❝ ▲❛♥❡✮ ❍ ✷ ❇ ❩ ❳ ❊①t ❇ ❳ ✇❤❡♥❡✈❡r ❊①t ❇ ❳ ✐s ♥♦t ❡♠♣t②✳ ❈♦♥s❡q✉❡♥❝❡s ♦❢ t❤❡ r❡♣r❡s❡♥t❛❜✐❧✐t② ♦❢ ❛❝t✐♦♥s ❚❤❡ r❡♣r❡s❡♥t❛❜✐❧✐t② ♦❢ ❛❝t✐♦♥s ❛❧❧♦✇s t❤❡ ❝❧❛ss✐✜❝❛t✐♦♥s ♦❢ ❡①t❡♥s✐♦♥s ✇✐t❤ ♥♦♥✲❛❜❡❧✐❛♥ ❦❡r♥❡❧✿ t♦ ❡✈❡r② ❡①t❡♥s✐♦♥ � ❆ ❢ � ❇ ❳ ✇❡ ❝❛♥ ❛ss♦❝✐❛t❡ ❛ ❤♦♠♦♠♦r♣❤✐s♠ ϕ : ❇ → ❖✉t ( ❳ ) = ❆✉t ( ❳ ) ■♥♥ ( ❳ ) ✱ t❤❡ ❛❜str❛❝t ❦❡r♥❡❧ ♦❢ t❤❡ ❡①t❡♥s✐♦♥✳

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Arithmetic Hall algebras Maxim Kontsevich I.H.E.S. 7 September 2019 1/19 Hall algebras and

Arithmetic Hall algebras Maxim Kontsevich I.H.E.S. 7 September 2019 1/19 Hall algebras and

Arithmetic Hall algebras Maxim Kontsevich I.H.E.S. 7 September 2019 1/19 Hall algebras and dilogarithm identities q = p r : power of a prime , F q : finite field , Q : finite quiver Gives an abelian category A with finite sets of morphisms and

309 views • 19 slides
Homotopy Type Theory and Algebraic Model Structures (I) Nicola Gambino School of Mathematics

Homotopy Type Theory and Algebraic Model Structures (I) Nicola Gambino School of Mathematics

Homotopy Type Theory and Algebraic Model Structures (I) Nicola Gambino School of Mathematics University of Leeds Topologie Alg ebrique et Applications Paris, 2nd December 2016 1 Plan of the talks Goal analysis of the cubical set

647 views • 36 slides
CPSC 504 Background (aka, all you need to know about databases for this course in two

CPSC 504 Background (aka, all you need to know about databases for this course in two

CPSC 504 Background (aka, all you need to know about databases for this course in two lectures) Rachel Pottinger January 8 and 12, 2015 Administrative notes Dont forget to sign up for a presentation day and a discussion day Anyone

1.17k views • 100 slides
Dependent type theory as the initial category with families Internship at Chalmers University of

Dependent type theory as the initial category with families Internship at Chalmers University of

Dependent type theory as the initial category with families Internship at Chalmers University of Technology, with Peter Dybjer and Thierry Coquand Simon Castellan December 8, 2014 Introduction Initiality : a term of ring theory (eg. 1 + 1)

619 views • 26 slides
On Baum Connes conjecture Homology KK G Kasparov product KK G -category Assembly Ryszard Nest

On Baum Connes conjecture Homology KK G Kasparov product KK G -category Assembly Ryszard Nest

On Baum Connes conjecture Ryszard Nest Non- commutative topology C*-algebras On Baum Connes conjecture Homology KK G Kasparov product KK G -category Assembly Ryszard Nest Baum-Connes conjecture Categorical reformulation University

693 views • 34 slides
Holomorphic symplectic fermions Ingo Runkel Hamburg University joint with Alexei Davydov

Holomorphic symplectic fermions Ingo Runkel Hamburg University joint with Alexei Davydov

Holomorphic symplectic fermions Ingo Runkel Hamburg University joint with Alexei Davydov Outline Investigate holomorphic extensions of symplectic fermions via embedding into a holomorphic VOA (existence) via study of commutative

1.1k views • 31 slides
Shifted symplectic derived algebraic geometry, and extensions of DonaldsonThomas theory

Shifted symplectic derived algebraic geometry, and extensions of DonaldsonThomas theory

Motives of d-critical loci DT style invariants for Calabi-Yau 4-folds Cohomological Hall Algebras Gluing matrix factorization categories Shifted symplectic derived algebraic geometry, and extensions of DonaldsonThomas theory Lecture 3 of

405 views • 12 slides
More lists Readings: HtDP , sections 11, 12, 13 (Intermezzo 2). Topics: Sorting a list List

More lists Readings: HtDP , sections 11, 12, 13 (Intermezzo 2). Topics: Sorting a list List

More lists Readings: HtDP , sections 11, 12, 13 (Intermezzo 2). Topics: Sorting a list List abbreviations Lists containing lists Dictionaries and association lists Lists of lists as 2D data Processing two lists simultaneously Consuming a

712 views • 25 slides
Analyzing similarity of multiple cloned software systems Slawomir Duszynski

Analyzing similarity of multiple cloned software systems Slawomir Duszynski

Analyzing similarity of multiple cloned software systems Slawomir Duszynski slawomir.duszynski@iese.fraunhofer.de Fraunhofer IESE Kaiserslautern, Germany November 28, 2011 The 16th CREST Open Workshop UCL London Motivation for Multi-System

355 views • 22 slides
Changes To AIRS Spectral Calibration For V6: A Progress Report Denis Elliott October 17,

Changes To AIRS Spectral Calibration For V6: A Progress Report Denis Elliott October 17,

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Atmospheric Infrared Sounder Changes To AIRS Spectral Calibration For V6: A Progress Report Denis Elliott

590 views • 30 slides
ACCOUNTING FOR CHANGE- NAVIGATING THE CORONAVIRUS HEADWINDS PRESENTED BY MOSS ADAMS Please

ACCOUNTING FOR CHANGE- NAVIGATING THE CORONAVIRUS HEADWINDS PRESENTED BY MOSS ADAMS Please

The Aerospace & Defense Forum National Online Forum April 30, 2020 ACCOUNTING FOR CHANGE- NAVIGATING THE CORONAVIRUS HEADWINDS PRESENTED BY MOSS ADAMS Please ensure your mike is muted and your video is off. Questions will be welcomed via

223 views • 19 slides
Quiz Parts 1 and 2: Describe two interpretations of the matrix-vector product A v , one involving

Quiz Parts 1 and 2: Describe two interpretations of the matrix-vector product A v , one involving

Quiz Parts 1 and 2: Describe two interpretations of the matrix-vector product A v , one involving rows and one involving columns. Part 3: Describe an interpretation of the matrix-matrix product AB , one involving either rows or columns. Parts 4

579 views • 31 slides
Machine Learning for Signal Processing Fundamentals of Linear Algebra - 2 Class 3. 8 Sep 2015

Machine Learning for Signal Processing Fundamentals of Linear Algebra - 2 Class 3. 8 Sep 2015

Machine Learning for Signal Processing Fundamentals of Linear Algebra - 2 Class 3. 8 Sep 2015 Instructor: Bhiksha Raj 11-755/18-797 1 Overview Vectors and matrices Basic vector/matrix operations Various matrix types

1.07k views • 78 slides
Machine Learning for Signal Processing Fundamentals of Linear Algebra - 2 Class 3. 8 Sep 2016

Machine Learning for Signal Processing Fundamentals of Linear Algebra - 2 Class 3. 8 Sep 2016

Machine Learning for Signal Processing Fundamentals of Linear Algebra - 2 Class 3. 8 Sep 2016 Instructor: Bhiksha Raj 11-755/18-797 1 Overview Vectors and matrices Vector spaces Basic vector/matrix operations Various matrix

2.61k views • 93 slides
1 Low-rank approximations to a matrix using SVD First point: we can write the SVD as a sum of

1 Low-rank approximations to a matrix using SVD First point: we can write the SVD as a sum of

Statistical Modeling and Analysis of Neural Data (NEU 560) Princeton University, Spring 2018 Jonathan Pillow Lecture 4 notes: PCA Thurs, 2.15 1 Low-rank approximations to a matrix using SVD First point: we can write the SVD as a sum of rank-1

363 views • 3 slides
Fukaya categories of symmetric products and bordered Heegaard-Floer homology Denis AUROUX

Fukaya categories of symmetric products and bordered Heegaard-Floer homology Denis AUROUX

Fukaya categories of symmetric products and bordered Heegaard-Floer homology Denis AUROUX Massachusetts Institute of Technology (work in progress) Ozsv ath-Szab o invariants as a TQFT? ( X ) Z closed 4-manifold X = ( HF

295 views • 14 slides
Numerical Linear Algebra EECS 442 David Fouhey Fall 2019, University of Michigan

Numerical Linear Algebra EECS 442 David Fouhey Fall 2019, University of Michigan

Numerical Linear Algebra EECS 442 David Fouhey Fall 2019, University of Michigan http://web.eecs.umich.edu/~fouhey/teaching/EECS442_W19/ Administrivia HW 1 out due in two weeks Follow submission format (wrong format = 0) The

1.62k views • 114 slides
BBM406 Fundamentals of Machine Learning Lecture 15: Support Vector Machines Aykut Erdem //

BBM406 Fundamentals of Machine Learning Lecture 15: Support Vector Machines Aykut Erdem //

Photo by Arthur Gretton, CMU Machine Learning Protestors at G20 BBM406 Fundamentals of Machine Learning Lecture 15: Support Vector Machines Aykut Erdem // Hacettepe University // Fall 2019 Announcement Midterm exam on Nov 29 Dec 6, 2019

695 views • 35 slides
Help help For PCs, Matlab should be a program. help command For Suns: Eg ., help

Help help For PCs, Matlab should be a program. help command For Suns: Eg ., help

Matlab tutorial and Linear Announcements Algebra Review Todays goals: Class mailing list: send email to Learn enough matlab to get started. Hyoungjune Yi: aster@cs .umd.edu Review some basics of Linear Algebra Homework at

334 views • 7 slides
Correlation Cohen Chapter 9 EDUC/PSY 6600 "Statistics is not a discipline like physics,

Correlation Cohen Chapter 9 EDUC/PSY 6600 "Statistics is not a discipline like physics,

Correlation Cohen Chapter 9 EDUC/PSY 6600 "Statistics is not a discipline like physics, chemistry, or biology where we study a subject to solve problems in the same subject. We study statistics with the main aim of solving problems in

563 views • 38 slides
Following the Energy Sectors Roadmap Carol Hawk CEDS R&D Program Manager Energy Sector

Following the Energy Sectors Roadmap Carol Hawk CEDS R&D Program Manager Energy Sector

Cybersecurity for Energy Delivery Systems (CEDS) R&D Following the Energy Sectors Roadmap Carol Hawk CEDS R&D Program Manager Energy Sector Cybersecurity Different Priorities Business IT Energy Delivery Systems Control

321 views • 19 slides
Causal Embeddings For Recommendation Stephen Bonner & Flavian Vasile Criteo Research

Causal Embeddings For Recommendation Stephen Bonner & Flavian Vasile Criteo Research

Causal Embeddings For Recommendation Stephen Bonner & Flavian Vasile Criteo Research September 28, 2018 Introduction Classical Recommendation approaches: A distance learning problem between pairs of products or between pairs of users

392 views • 20 slides
Software Evolvability: An industrys view 2 nd Open Workshop on Resilience in Computing Systems

Software Evolvability: An industrys view 2 nd Open Workshop on Resilience in Computing Systems

Software Evolvability: An industrys view 2 nd Open Workshop on Resilience in Computing Systems and Information Infrastructures Author: Giuseppe Martufi giuseppe.martufi@elsagdatamat.com 18/10/2007 ReSIST workshop, Rome 18 Oct 07 What is

545 views • 7 slides
Community Based Climate Change Adaptation: a Case of Community Forestry Programme of Nepal.

Community Based Climate Change Adaptation: a Case of Community Forestry Programme of Nepal.

Community Based Climate Change Adaptation: a Case of Community Forestry Programme of Nepal. UNU-WIDER Conference on Climate Change and Development Policy 28-29 September 2012, Helsinki, Finland Nirmal kumar Bishokarma Kathmandu

352 views • 17 slides

More recommend