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2016-09-27
Symposium: East Asia: Where Are Things Headed? - April 29, 2016
source: Harvard University 2016年8月23日
Moderator: Susan Pharr
Edwin O. Reischauer Professor of Japanese Politics and Director, WCFIA Program on U.S.-Japan Relations, Harvard University
Speakers:
Akio Takahara
Professor, Faculty of Law and Graduate School of Law and Politics, University of Tokyo
Victor Cha
D.S. Song-KF Endowed Chair in Government and International Affairs, Georgetown University, and Senior Advisor and Korea Chair, Center for Strategic and International Studies (CSIS)
Sheila Smith
Senior Fellow for Japan Studies, Council on Foreign Relations
Zheng Wang
Associate Professor and Director, Center for Peace and Conflict Studies, School of Diplomacy and International Relations, Seton Hall University
Location:
Belfer Case Study Room (S020), Japan Friends of Harvard Concourse, CGIS South Building, 1730 Cambridge Street
Time: 12:30 - 2:00 pm
Co-sponsored by Harvard University Asia Center, Fairbank Center for Chinese Studies, Korea Institute, Edwin O. Reischauer Institute of Japanese Studies, Harvard Kennedy School Japan Caucus, and Japan Society of Boston.
This symposium is supported by a generous grant from the Japan Foundation Center for Global Partnership (CGP).
Evolution of Architecture and Landscape at Stanford
source: Stanford 2016年8月22日
University Architect David Lenox described the historic evolution of the campus and its architecture from its earliest incarnations to its current state, and provided a glimpse into the future development of the campus. Chris Wasney ‘80 presented some of his firm's work on buildings from virtually all of the eras of Stanford's development.
Reality Begins with Consciousness with Vernon Neppe
source: New Thinking Allowed 2016年5月19日
Vernon Neppe, MD, PhD, FRSSAf, is a neuropsychiatrist and head of the Pacific Neuropsychiatric Institute in Seattle. He is author, with physicist Edward Close, of Reality Begins with Consciousness: A Paradigm Shift that Works. He is also author of Déjà Vu Revisited, Déjà Vu: A Second Look, Déjà Vu: Glossary and Library, Cry the Beloved Mind: A Voyage of Hope, and Innovative Psychopharmacotherapy. His professional publications number over 700. Dr Neppe has amplified many of his concepts in two of the websites linked with his work. On www.Brainvoyage.com, his books are amplified. www.VernonNeppe.org is his gateway and includes more information on the Neppe-Close model of the Triadic Distinction Vortical Paradigm.
Dr. Vernon Neppe refers to his theoretical work as a “new paradigm”. By looking at nine, discreet, finite dimensions he is able to show the relationship between the finite and the infinite. His mathematical model calls for a third entity, in addition to matter and energy, called “gimmel” and which may be an expression of the contents of consciousness. Because his work challenges so many commonly held beliefs, it is difficult for many people to comprehend. However, it offers the potential for understanding the nature of consciousness, life, and paranormal phenomena.
New Thinking Allowed host, Jeffrey Mishlove, PhD, is author of The Roots of Consciousness, Psi Development Systems, and The PK Man. Between 1986 and 2002 he hosted and co-produced the original Thinking Allowed public television series. He is the recipient of the only doctoral diploma in "parapsychology" ever awarded by an accredited university (University of California, Berkeley, 1980). He is also past-president of the non-profit Intuition Network, an organization dedicated to creating a world in which all people are encouraged to cultivate and apply their inner, intuitive abilities.
(Recorded on April 17, 2016)
The history of the Cuban Missile Crisis - Matthew A. Jordan
source: TED-Ed 2016年9月26日
View full lesson: http://ed.ted.com/lessons/the-history...
Imagine going about your life knowing that, at any given moment, you and everyone you know could be wiped out without warning at the push of a button. This was the reality for millions of people during the forty-five year period after World War II now known as the Cold War. Matthew A. Jordan explains the history behind the peak of all this panic — the thirteen days of the Cuban Missile Crisis.
Lesson by Mathew A. Jordan, animation by Patrick Smith.
Electronics - Pattern Recognition by P. S. Sastry (IISc Bangalore)
# click the upper-left icon to select videos from the playlist
source: nptelhrd 2013年12月1日
Electronics - Pattern Recognition by Prof. P. S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more details on NPTEL visit http://nptel.ac.in
28 Feedforward networks for Classification and Regression; Backpropagation in Practice 58:40
13 Linear Discriminant Functions; Perceptron -- Learning Algorithm and convergence proof 58:22
40 Bootstrap, Bagging and Boosting; Classifier Ensembles; AdaBoost 59:31
12 Nonparametric estimation, Parzen Windows, nearest neighbour methods 57:30
39 Assessing Learnt classifiers; Cross Validation; 59:50
27 Backpropagation Algorithm; Representational abilities of feedforward networks 59:01
26 Multilayer Feedforward Neural networks with Sigmoidal activation functions; 58:57
25 Overview of Artificial Neural Networks 59:11
38 No Free Lunch Theorem; Model selection and model estimation; Bias-variance trade-off 59:53
24 VC-Dimension Examples; VC-Dimension of hyperplanes 59:00
11 Convergence of EM algorithm; overview of Nonparametric density estimation 58:18
37 Feature Selection and Dimensionality Reduction; Principal Component Analysis 59:14
23 Complexity of Learning problems and VC-Dimension 58:38
10 Mixture Densities, ML estimation and EM algorithm 57:27
36 Positive Definite Kernels; RKHS; Representer Theorem 58:46
09 Sufficient Statistics; Recursive formulation of ML and Bayesian estimates 58:07
22 Consistency of Empirical Risk Minimization; VC-Dimension 58:14
35 Overview of SMO and other algorithms for SVM; ?-SVM and ?-SVR; SVM as a risk minimizer 58:29
08 Bayesian Estimation examples; the exponential family of densities and ML estimates 57:05
34 Support Vector Regression and ?-insensitive Loss function, examples of SVM learning 58:40
07 Bayesian estimation of parameters of density functions, MAP estimates 57:06
21 Consistency of Empirical Risk Minimization 58:35
20 Overview of Statistical Learning Theory; Empirical Risk Minimization 58:53
19 Learning and Generalization; PAC learning framework 59:02
06 Maximum Likelihood estimation of different densities 58:16
33 Kernel Functions for nonlinear SVMs; Mercer and positive definite Kernels 58:45
05 Implementing Bayes Classifier; Estimation of Class Conditional Densities 58:08
18 Linear Discriminant functions for multi-class case; multi-class logistic regression 57:24
04 Estimating Bayes Error; Minimax and Neymann-Pearson classifiers 57:16
32 SVM formulation with slack variables; nonlinear SVM classifiers 59:00
source: nptelhrd 2013年12月1日
Electronics - Pattern Recognition by Prof. P. S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more details on NPTEL visit http://nptel.ac.in
28 Feedforward networks for Classification and Regression; Backpropagation in Practice 58:40
13 Linear Discriminant Functions; Perceptron -- Learning Algorithm and convergence proof 58:22
40 Bootstrap, Bagging and Boosting; Classifier Ensembles; AdaBoost 59:31
12 Nonparametric estimation, Parzen Windows, nearest neighbour methods 57:30
39 Assessing Learnt classifiers; Cross Validation; 59:50
27 Backpropagation Algorithm; Representational abilities of feedforward networks 59:01
26 Multilayer Feedforward Neural networks with Sigmoidal activation functions; 58:57
25 Overview of Artificial Neural Networks 59:11
38 No Free Lunch Theorem; Model selection and model estimation; Bias-variance trade-off 59:53
24 VC-Dimension Examples; VC-Dimension of hyperplanes 59:00
11 Convergence of EM algorithm; overview of Nonparametric density estimation 58:18
37 Feature Selection and Dimensionality Reduction; Principal Component Analysis 59:14
23 Complexity of Learning problems and VC-Dimension 58:38
10 Mixture Densities, ML estimation and EM algorithm 57:27
36 Positive Definite Kernels; RKHS; Representer Theorem 58:46
09 Sufficient Statistics; Recursive formulation of ML and Bayesian estimates 58:07
22 Consistency of Empirical Risk Minimization; VC-Dimension 58:14
35 Overview of SMO and other algorithms for SVM; ?-SVM and ?-SVR; SVM as a risk minimizer 58:29
08 Bayesian Estimation examples; the exponential family of densities and ML estimates 57:05
34 Support Vector Regression and ?-insensitive Loss function, examples of SVM learning 58:40
07 Bayesian estimation of parameters of density functions, MAP estimates 57:06
21 Consistency of Empirical Risk Minimization 58:35
20 Overview of Statistical Learning Theory; Empirical Risk Minimization 58:53
19 Learning and Generalization; PAC learning framework 59:02
06 Maximum Likelihood estimation of different densities 58:16
33 Kernel Functions for nonlinear SVMs; Mercer and positive definite Kernels 58:45
05 Implementing Bayes Classifier; Estimation of Class Conditional Densities 58:08
18 Linear Discriminant functions for multi-class case; multi-class logistic regression 57:24
04 Estimating Bayes Error; Minimax and Neymann-Pearson classifiers 57:16
32 SVM formulation with slack variables; nonlinear SVM classifiers 59:00
PHIL 10 - Introduction to Logic by Rick Grush (UC San Diego)
# click the up-left corner to select videos from the playlist
source: Introduction to Logic, Philosophy 10, UC San Diego 2015年1月10日
Lectures of Introduction to Logic, Philosophy 10, UC San Diego.
0. Introductory Lecture 25:16
3. Ch. 1 (Part 3/3). BSLIF 27:57
2. Ch. 1 (Part 2/3). BSLIF 39:04
1. Ch. 1 (Part 1/3) BSLIF 39:56
10.Ch. 4, Sections 4.1-4.5.BSLIF 41:54
11. Ch. 4, Section 4.6. BSLIF 22:47
12. Ch. 4, Section 4.7. BSLIF 26:36
13. Ch. 4, Sections 4.8 & 4.9. BSLIF 22:44
9. Ch. 3, Sections 3.5 & 3.6. BSLIF 26:08
8b. Ch. 3, Section 3.4. BSLIF 22:27
7. Ch. 3, Sections 3.1 & 3.2. BSLIF 29:26
6. Ch. 2, Sections 2.4 & 2.5. BSLIF 43:33
5. Ch. 2, Sections 2.2 & 2.3. BSLIF 40:24
Practice Exam 1. 22:53
Practice Exam 2. 25:36
Practice Exam 3. 15:36
Practice Exam 4. 20:22
Practice Final (Part 2/3). 26:14
Practice Final (Part 3/3). 47:44
source: Introduction to Logic, Philosophy 10, UC San Diego 2015年1月10日
Lectures of Introduction to Logic, Philosophy 10, UC San Diego.
0. Introductory Lecture 25:16
3. Ch. 1 (Part 3/3). BSLIF 27:57
2. Ch. 1 (Part 2/3). BSLIF 39:04
1. Ch. 1 (Part 1/3) BSLIF 39:56
10.Ch. 4, Sections 4.1-4.5.BSLIF 41:54
11. Ch. 4, Section 4.6. BSLIF 22:47
12. Ch. 4, Section 4.7. BSLIF 26:36
13. Ch. 4, Sections 4.8 & 4.9. BSLIF 22:44
9. Ch. 3, Sections 3.5 & 3.6. BSLIF 26:08
8b. Ch. 3, Section 3.4. BSLIF 22:27
7. Ch. 3, Sections 3.1 & 3.2. BSLIF 29:26
6. Ch. 2, Sections 2.4 & 2.5. BSLIF 43:33
5. Ch. 2, Sections 2.2 & 2.3. BSLIF 40:24
Practice Exam 1. 22:53
Practice Exam 2. 25:36
Practice Exam 3. 15:36
Practice Exam 4. 20:22
Practice Final (Part 2/3). 26:14
Practice Final (Part 3/3). 47:44
John Dupré and Alex Rosenberg: Reductionism & Non-Reductionist Physicalism
source: Philosophical Overdose 2013年3月29日
John Dupré and Alex Rosenberg discuss physicalist reductionism & anti-reductionism. According to physicalism (materialism), nothing which exists is non-physical, immaterial, spiritual, or otherwise incorporeal. According to reductionism, all facts can be captured by some purely physical description of the world. So are mental properties reducible to physical properties in this sense? Are psychology and the other social sciences reducible to biology and physics? In this debate, Dupré defends the more orthodox view, while Rosenberg defends the less popular view: physicalist reductionism. They also discuss some of the issues for both views. Reductionism faces, for instance, the problem of multiple realizability (i.e. how the very same mental states could occur in organisms which have very different physical constitutions). And non-reductionism faces the problem of causal exclusion or overdetermination (i.e. how mental states could play any explanatory or causal role given that the universe is causally closed and everything is entirely caused by physical causes).
This is from Philosophy TV. For more information, go to www.philostv.com.
Atul Singh: "The Global Rise of the Far Right" | Talks at Google
source: Talks at Google 2016年8月15日
From Japan and Philippines to the UK and the US, nationalism is on the rise. This is transforming politics by enabling the rise of the right and, more alarmingly, of the far-right.
Before we carry on, what do we mean by the right and the far-right? To understand this, we have to go back to the heady days of the French Revolution. In the French parliament, supporters of l'Ancien Régime sat on the right while those who wanted a secular republic with equality for all sat on the left. Those who sat on the right believed in hierarchy, tradition and clericalism. Inequality and social stratification were the natural order of the universe.
Over time, the justification for some being more equal than others has changed from noble birth to ability and hard work. Those who win in a competitive free market deserve greater rewards for their ingenuity and industriousness. The right broadly believes that markets produce better outcomes than governments and that inequality is a price worth paying for efficiency, choice and greater wealth for all.
The far-right takes ideas of inequality and stratification to absurd levels. It often ascribes an entire nation or race as superior. The Nazi Party famously deemed Germans belonging to the Aryan race as the master race. In contrast, Jews, Slavs and many others were mere untermenschen. The Nazis were part of a long European tradition of such extreme ideas. The British believed they were superior to the yellow opium addicts in China and the brown idol worshippers in India. Belgian King Leopold II believed that his countrymen had a divine right to slaughter, torture and pillage the half-humans who inhabited the heart of darkness in Congo.
After decades of relative obscurity and quiescence, the far-right finds itself back in the fray. In Philippines, President Rodrigo Duterte is urging people to kill drug addicts. Austria faces another election where a Glock 9mm pistol-packing Norbert Hofer has a fair shot at the presidency. In France, Marine Le Pen is the respectable face of the immigrant-bashing far-right. The UK has just voted for Brexit thanks in no small part to the exhortations of xenophobes like Nigel Farage. In the US, the rise of Donald Trump, a tacky billionaire and reality television star, is confounding political analysts and sending shivers down spines of minorities such as Muslims and Mexicans.
As this speaker wrote not too long ago, this is an age of fear, anger, hate and terror. The scale and pace of change is faster than ever. Inequality is rising incessantly not only in terms of income and wealth but also in terms of education and opportunity. Social mobility has taken a battering. Institutions are increasingly crumbling around the world. There is a growing dichotomy between global aspiration and local impoverishment. This puts collective identities in question. Is it nation, region, ethnicity, race or religion?
Far-right leaders are touching upon deep seated fears and providing simplistic solutions to complex problems. They are rising to the fore because elites are empty and exhausted. These elites have been narrow and technocratic. They have tried to kick the can down the road and dodged big questions. Most importantly, they have failed to articulate a vision with a compelling collective narrative and people feel lost. It is a most dangerous time for the planet as temperatures increase, sea levels rise and people turn to demagogues for quick fixes.
Atul Singh Bio:
Atul Singh is the Founder, CEO and Editor-in-Chief of Fair Observer. He teaches Political Economy at the University of California, Berkeley and at the Indian Institute of Technology, Gandhinagar where he also teaches World History. He studied Philosophy, Politics and Economics at Oxford on the Radhakrishnan Scholarship and did an MBA with a triple major in finance, strategy and entrepreneurship at the Wharton School. Singh worked as a corporate lawyer in London and led special operations as an elite officer in India’s volatile border areas where he had many near-death experiences. He has also been a poet, playwright, sportsman, mountaineer and a founder of many organizations. Singh’s knowledge is eclectic, and his friends often joke that it comes in handy when access to Google is limited.
How to Think Like an FBI Negotiator? Use Empathy | Chris Voss
source: Big Think 2016年8月22日
Former FBI negotiator Chris Voss sheds light on communication and indirect messages, the value of empathy in business and in life, and when and how to walk away from a deal. Chris Voss is the author of "Never Split the Difference: Negotiating as If Your Life Depended on It" (http://goo.gl/04OgLC).
Read more at BigThink.com: http://bigthink.com/videos/chris-voss...
Transcript - The best messages in any given negotiation are really implied indirectly, come to the other person based on thinking that you're getting them to do, getting them to get some really solid thought behind their answers. And so a great thing to send someone in an email is have you given up on this project? Because nobody likes to give up on anything, and at the same time nobody wants to say yes to that because they don't know what they're letting themselves in for when they say yes.
You know, and it's interesting because that particular email has restarted negotiations that have seen dead silence for weeks prior to that. And simply sending that email all by itself, and in many cases you can get a response within three to five minutes of reading the email or the text, that's a great way to get things restarted. Now the problem with that is there's a really good chance you contributed to the silence in the first place. And your next move, when they respond, is you've got to get a that's right out of them next because they have to feel like that their communication is being paid attention to. Read Full Transcript Here: http://goo.gl/D5BEFj.
Riemann Hypothesis and its Applications by Manindra Agrawal (IIT Kanpur)
# click the upper-left icon to select videos from the playlist
source: nptelhrd 2014年10月8日
Computer Science - Riemann Hypothesis and its Applications by Prof. Manindra Agrawal, Department of Computer Science and Engineering, IIT Kanpur. For more details on NPTEL visit http://nptel.ac.in.
Mod-01 Lec-01 41:44
Mod-01 Lec-02 50:21
Mod-01 Lec-03 45:23
Mod-01 Lec-04 46:20
Mod-01 Lec-05 46:31
Mod-01 Lec-06 59:09
Mod-01 Lec-07 51:16
Mod-01 Lec-08 50:56
Mod-01 Lec-09 57:51
Mod-01 Lec-10 49:16
Mod-01 Lec-11 43:26
Mod-01 Lec-12 55:09
Mod-01 Lec-13 51:13
Mod-01 Lec-14 38:16
Mod-01 Lec-15 51:53
Mod-01 Lec-16 57:42
Mod-01 Lec-17 50:34
Mod-01 Lec-18 55:29
Mod-01 Lec-19 43:46
Mod-01 Lec-20 1:20:57
Mod-01 Lec-21 43:00
Mod-01 Lec- 22 38:34
Mod-01 Lec- 23 37:54
Mod-01 Lec-24 40:23
Mod-01 Lec-25 42:37
Mod-01 Lec-26 34:01
Mod-01 Lec-27 1:28:54
Mod-01 Lec-28 54:20
Mod-01 Lec-29 27:32
Mod-01 Lec-30 35:34
source: nptelhrd 2014年10月8日
Computer Science - Riemann Hypothesis and its Applications by Prof. Manindra Agrawal, Department of Computer Science and Engineering, IIT Kanpur. For more details on NPTEL visit http://nptel.ac.in.
Mod-01 Lec-01 41:44
Mod-01 Lec-02 50:21
Mod-01 Lec-03 45:23
Mod-01 Lec-04 46:20
Mod-01 Lec-05 46:31
Mod-01 Lec-06 59:09
Mod-01 Lec-07 51:16
Mod-01 Lec-08 50:56
Mod-01 Lec-09 57:51
Mod-01 Lec-10 49:16
Mod-01 Lec-11 43:26
Mod-01 Lec-12 55:09
Mod-01 Lec-13 51:13
Mod-01 Lec-14 38:16
Mod-01 Lec-15 51:53
Mod-01 Lec-16 57:42
Mod-01 Lec-17 50:34
Mod-01 Lec-18 55:29
Mod-01 Lec-19 43:46
Mod-01 Lec-20 1:20:57
Mod-01 Lec-21 43:00
Mod-01 Lec- 22 38:34
Mod-01 Lec- 23 37:54
Mod-01 Lec-24 40:23
Mod-01 Lec-25 42:37
Mod-01 Lec-26 34:01
Mod-01 Lec-27 1:28:54
Mod-01 Lec-28 54:20
Mod-01 Lec-29 27:32
Mod-01 Lec-30 35:34
Graph Theory by L. Sunil Chandran (IISc Bangalore)
# click the upper-left icon to select videos from the playlist
source: nptelhrd 2012年5月21日
Computer - Graph Theory by Dr. L. Sunil Chandran, Department of Computer Science and Automation, IISc Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
01 Introduction: Vertex cover and independent set 56:13
02 Matchings: Konig's theorem and Hall's theorem 58:27
03 More on Hall's theorem and some applications 57:38
04 Tutte's theorem on existence of a perfect matching 58:07
05 More on Tutte's theorem 58:10
06 More on Matchings 57:58
07 Dominating set, path cover 58:45
08 Gallai -- Millgram theorem, Dilworth's theorem 57:51
09 Connectivity: 2-connected and 3- connected graphs 58:03
10 Menger's theorem 56:17
11 More on connectivity: k- linkedness 55:28
12 Minors, topological minors and more on k- linkedness 55:33
13 Vertex coloring: Brooks theorem 57:21
14 More on vertex coloring 55:34
15 Edge coloring: Vizing's theorem 56:36
16 Proof of Vizing's theorem, Introduction to planarity 56:52
17 5- coloring planar graphs, Kuratowsky's theorem 57:32
18 Proof of Kuratowsky's theorem, List coloring 56:48
19 List chromatic index 57:37
20 Adjacency polynomial of a graph and combinatorial Nullstellensatz 56:30
21 Chromatic polynomial, k - critical graphs 57:07
22 Gallai-Roy theorem, Acyclic coloring, Hadwiger's conjecture 54:03
23 Perfect graphs: Examples 57:24
24 Interval graphs, chordal graphs 57:08
25 Proof of weak perfect graph theorem (WPGT) 56:35
26 Second proof of WPGT, Some non-perfect graph classes 57:48
27 More special classes of graphs 57:38
28 Boxicity,Sphericity, Hamiltonian circuits 57:02
29 More on Hamiltonicity: Chvatal's theorem 57:36
30 Chvatal's theorem, toughness, Hamiltonicity and 4-color conjecture 59:00
31 Network flows: Max flow mincut theorem 57:52
32 More on network flows: Circulations 58:35
33 Circulations and tensions 58:20
34 More on circulations and tensions, flow number and Tutte's flow conjectures 56:50
35 Random graphs and probabilistic method: Preliminaries 57:25
36 Probabilistic method: Markov's inequality, Ramsey number 57:34
37 Probabilistic method: Graphs of high girth and high chromatic number 58:20
38 Probabilistic method: Second moment method, Lovasz local lemma 58:50
39 Graph minors and Hadwiger's conjecture 58:28
40 More on graph minors, tree decompositions 58:31
source: nptelhrd 2012年5月21日
Computer - Graph Theory by Dr. L. Sunil Chandran, Department of Computer Science and Automation, IISc Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
01 Introduction: Vertex cover and independent set 56:13
02 Matchings: Konig's theorem and Hall's theorem 58:27
03 More on Hall's theorem and some applications 57:38
04 Tutte's theorem on existence of a perfect matching 58:07
05 More on Tutte's theorem 58:10
06 More on Matchings 57:58
07 Dominating set, path cover 58:45
08 Gallai -- Millgram theorem, Dilworth's theorem 57:51
09 Connectivity: 2-connected and 3- connected graphs 58:03
10 Menger's theorem 56:17
11 More on connectivity: k- linkedness 55:28
12 Minors, topological minors and more on k- linkedness 55:33
13 Vertex coloring: Brooks theorem 57:21
14 More on vertex coloring 55:34
15 Edge coloring: Vizing's theorem 56:36
16 Proof of Vizing's theorem, Introduction to planarity 56:52
17 5- coloring planar graphs, Kuratowsky's theorem 57:32
18 Proof of Kuratowsky's theorem, List coloring 56:48
19 List chromatic index 57:37
20 Adjacency polynomial of a graph and combinatorial Nullstellensatz 56:30
21 Chromatic polynomial, k - critical graphs 57:07
22 Gallai-Roy theorem, Acyclic coloring, Hadwiger's conjecture 54:03
23 Perfect graphs: Examples 57:24
24 Interval graphs, chordal graphs 57:08
25 Proof of weak perfect graph theorem (WPGT) 56:35
26 Second proof of WPGT, Some non-perfect graph classes 57:48
27 More special classes of graphs 57:38
28 Boxicity,Sphericity, Hamiltonian circuits 57:02
29 More on Hamiltonicity: Chvatal's theorem 57:36
30 Chvatal's theorem, toughness, Hamiltonicity and 4-color conjecture 59:00
31 Network flows: Max flow mincut theorem 57:52
32 More on network flows: Circulations 58:35
33 Circulations and tensions 58:20
34 More on circulations and tensions, flow number and Tutte's flow conjectures 56:50
35 Random graphs and probabilistic method: Preliminaries 57:25
36 Probabilistic method: Markov's inequality, Ramsey number 57:34
37 Probabilistic method: Graphs of high girth and high chromatic number 58:20
38 Probabilistic method: Second moment method, Lovasz local lemma 58:50
39 Graph minors and Hadwiger's conjecture 58:28
40 More on graph minors, tree decompositions 58:31
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