PPT-Sublinear Algorithmic Tools

3 Alex Andoni Plan 2 Dimension reduction Application Numerical Linear Algebra Sketching Application Streaming Application Nearest Neighbor Search and more Dimension reduction linear . Lovasz. Local Lemma.  . Nick Harvey. University of British Columbia. Jan . Vondrak. IBM . Almaden. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. Let . 1. Decision Procedures. An Algorithmic Point of View. BDDs. Decision Procedures . An algorithmic point of view. 2. Binary . Decision Diagrams. SAT. looked for a . satisfying solution. to CNF. We will now examine a graph-based data structure called . Talya Eden, . Tel Aviv . University. Amit Levi, . University of Waterloo. Dana . Ron, . Tel Aviv . University. C. . Seshadhri. , . UC Santa Cruz. Counting Triangles. Basic graph-theoretic algorithmic . NAS-Royal Society . Sackler. Forum , The Frontiers of Machine Learning. Washington DC, 31 Jan-2 February 2017. Professor Karen Yeung. Director, Centre for Technology, Ethics, Law & Society (TELOS). Huijia. Lin (USB), . Rafael Pass . (Cornell). Karn. . Seth . (Cornell -> Google). Sid . Telang. (Cornell -> Google). IO. Plethora of Applications. For example: SW14, BCP14, BZ14, GGHR14, BGL. Lecture . 10: . Sublinear. Algorithm. Zhu Han. University of Houston. Thanks for Professor Dan Wang’s slides. 1. outline. Motivations. Inequalities and classifications . Examples. Applications. 2. Talya Eden, . Tel Aviv . University. Amit Levi, . University of Waterloo. Dana . Ron, . Tel Aviv . University. C. . Seshadhri. , . UC Santa Cruz. Counting Triangles. Basic graph-theoretic algorithmic . EECT 7327 . Fall 2014. Algorithmic . (Cyclic) ADC. Algorithmic (Cyclic) ADC. – . 2. –. Data Converters Algorithmic ADC Professor Y. Chiu. EECT 7327 . Fall 2014. Input is sampled first, then circulates in the loop for N clock cycles. 2. Alex Andoni. Plan. 2. Dimension reduction. Application: Numerical Linear Algebra. Sketching. Application: Streaming. Application: Nearest Neighbor Search. and more…. Dimension reduction: . linear . Lecture . 10: . Sublinear. Algorithm. Zhu Han. University of Houston. Thanks for Professor Dan Wang’s slides. 1. outline. Motivations. Inequalities and classifications . Examples. Applications. 2. Holography. Or . How I learned to stop worrying and love the analytic gradient. . Wesley E. Farriss and James R. . Fienup. Clrc. . 2018. Okinawa, Japan. The Benefits of Reading Books,Most people read to read and the benefits of reading are surplus. But what are the benefits of reading. Keep reading to find out how reading will help you and may even add years to your life!.The Benefits of Reading Books,What are the benefits of reading you ask? Down below we have listed some of the most common benefits and ones that you will definitely enjoy along with the new adventures provided by the novel you choose to read.,Exercise the Brain by Reading .When you read, your brain gets a workout. You have to remember the various characters, settings, plots and retain that information throughout the book. Your brain is doing a lot of work and you don’t even realize it. Which makes it the perfect exercise! Block Sparse Fourier Transform. Volkan. . Cevher. Michael . Kapralov. Jonathan Scarlett. Amir . Zandieh. EPFL. 1. Discrete Fourier transform. . . root of unity . Fast Fourier Transform. Andy Crabtree. www.andy-crabtree.com. Right to an Explanation. GDPR and ‘explainable’ algorithmic machines. AI Will Have to Explain Itself . “The need for Explainable AI is being driven by upcoming regulations, like the European Union’s General Data Protection Regulation (GDPR), which requires explanations for decisions … Under the GDPR, there are hefty penalties for inaccurate explanations – making it imperative that companies correctly explain the decisioning process of its AI and ML systems, every time.” .