- 141
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Kiseki No Sedai
India
เข้าร่วมเมื่อ 11 พ.ย. 2021
Here i post theoretical computer science course lectures which is not available in youtube or the conference talks which are not available in youtube
วีดีโอ
Lecture 8 Part 3/3
มุมมอง 45 หลายเดือนก่อน
Lecture 8 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 23, 2011 - 16:15-19:15 - A journey in the wonderland of expanders • Edge-expansion • Examples of application • Spectral definition • Spectrum and expansion • Embeddings • Random walks • Examples of applications
Lecture 8 Part 2/3
มุมมอง 55 หลายเดือนก่อน
Lecture 8 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 23, 2011 - 16:15-19:15 - A journey in the wonderland of expanders • Edge-expansion • Examples of application • Spectral definition • Spectrum and expansion • Embeddings • Random walks • Examples of applications
Lecture 8 Part 1/3
มุมมอง 55 หลายเดือนก่อน
Lecture 8 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 23, 2011 - 16:15-19:15 - A journey in the wonderland of expanders • Edge-expansion • Examples of application • Spectral definition • Spectrum and expansion • Embeddings • Random walks • Examples of applications
Lecture 7 Part 2/3
มุมมอง 25 หลายเดือนก่อน
Lecture 7 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 16, 2011 - 16:15-19:15 - Exhaustive Sampling • Exhaustive guessing: a polynomial time randomized (1 ε)-approximation (PTRAS) for Max-CUT in dense graphs
Lecture 7 Part 3/3
มุมมอง 35 หลายเดือนก่อน
Lecture 7 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 16, 2011 - 16:15-19:15 - Exhaustive Sampling • Exhaustive guessing: a polynomial time randomized (1 ε)-approximation (PTRAS) for Max-CUT in dense graphs
Lecture 7 Part 1/3
มุมมอง 25 หลายเดือนก่อน
Lecture 7 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 16, 2011 - 16:15-19:15 - Exhaustive Sampling • Exhaustive guessing: a polynomial time randomized (1 ε)-approximation (PTRAS) for Max-CUT in dense graphs
Lecture 6 Part 3/3
มุมมอง 25 หลายเดือนก่อน
Lecture 6 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 2, 2011 - 16:15-19:15 - Exhaustive Sampling • A constant time (1 ε)-approximation for the size of a maximal matching in constant maximum degree graphs • Exhaustive guessing 1: a polynomial time randomized (1 ε)-approximation (PTRAS) for Max-CUT in dense graphs
Lecture 6 Part 2/3
มุมมอง 35 หลายเดือนก่อน
Lecture 6 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 2, 2011 - 16:15-19:15 - Exhaustive Sampling • A constant time (1 ε)-approximation for the size of a maximal matching in constant maximum degree graphs • Exhaustive guessing 1: a polynomial time randomized (1 ε)-approximation (PTRAS) for Max-CUT in dense graphs
Lecture 6 Part 1/3
มุมมอง 35 หลายเดือนก่อน
Lecture 6 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Feb 2, 2011 - 16:15-19:15 - Exhaustive Sampling • A constant time (1 ε)-approximation for the size of a maximal matching in constant maximum degree graphs • Exhaustive guessing 1: a polynomial time randomized (1 ε)-approximation (PTRAS) for Max-CUT in dense graphs
Lecture 5 Part 3/3
มุมมอง 35 หลายเดือนก่อน
Lecture 5 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Jan 26, 2011 - 16:15-19:15 - Guessing by sampling 2 • Application of linearity testing and self-correcting: NP is in PCP(poly(n),1) - QUADEQ is NP-complete - A PCP(n^2,1)-verifier for QUADEQ • A constant time (1 ε)-approximation for the size of a maximal matching in a constant degree graph
Lecture 5 Part 2/3
มุมมอง 25 หลายเดือนก่อน
Lecture 5 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Jan 26, 2011 - 16:15-19:15 - Guessing by sampling 2 • Application of linearity testing and self-correcting: NP is in PCP(poly(n),1) - QUADEQ is NP-complete - A PCP(n^2,1)-verifier for QUADEQ • A constant time (1 ε)-approximation for the size of a maximal matching in a constant degree graph
Lecture 5 Part 1/3
มุมมอง 55 หลายเดือนก่อน
Lecture 5 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Jan 26, 2011 - 16:15-19:15 - Guessing by sampling 2 • Application of linearity testing and self-correcting: NP is in PCP(poly(n),1) - QUADEQ is NP-complete - A PCP(n^2,1)-verifier for QUADEQ • A constant time (1 ε)-approximation for the size of a maximal matching in a constant degree graph
Lecture 4 Part 3/3
5 หลายเดือนก่อน
Lecture 4 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Jan 12, 2011 - 16:15-19:15 - Guessing by sampling • A lot of certificates puts Zero-P in BPP • The presence of a lot of certificates allows linearity testing • Random self-reduction allows linearity self-correcting
Lecture 4 Part 2/3
5 หลายเดือนก่อน
Lecture 4 MPRI Paris Master of Computer Science (Université Paris Diderot) by Nicolas Schabanel Jan 12, 2011 - 16:15-19:15 - Guessing by sampling • A lot of certificates puts Zero-P in BPP • The presence of a lot of certificates allows linearity testing • Random self-reduction allows linearity self-correcting
Professor Alex Lubotzky was the first to introduce this notion based on the proof using P-adic numbers. I have been thinking about its applications in Quantum Gravity ever since. Amazing that there have not been more likes and views than there are. This is an exciting topic and definitely worthy of a wider audience and following!
Beautiful start with the Fano plane!
Challenging for us to know further.Thank you.
Nice to see it
Bhai aap CMI ke ho?
1:10-2:45;16:20-21:47;37:31-38:03; 44:04-46:02;48:52-49:40;1:10:57-1:12:24; total 6.
Superb … prof Ram murti just awesome 😎 ❤
Dear Professor, and dear uploader, thank you!
improve your English
Very informative and can be applied in ophthalmology consideration the expectation of Ophthalmologist. Can an Ophthalmologist join the group