'Log log' presentation slideshows

Streaming Algorithms for Geometric Problems

Streaming Algorithms for Geometric Problems. Piotr Indyk MIT. Data Streams. A data stream is a (massive) sequence of data Too large to store (on disk, memory, cache, etc.) Examples: Network traffic (source/destination) Sensor networks Satellite data feed, etc. Approaches: Ignore it

607 views • 47 slides

Finding Nearby Objects in Peer-to-Peer Networks

Finding Nearby Objects in Peer-to-Peer Networks. Kirsten Hildrum. Object Location. The Big Picture. Behind the Cloud. ?. One directory One participant stores a lot, but average is low Stretch is high Everyone has a directory Low stretch! Everyone has lots of data

532 views • 40 slides

Solving Laplacian Systems: Some Contributions from Theoretical Computer Science

460 views • 32 slides

Growth Rates

Growth Rates. Growth rates of functions: Linear ? n Quadratic ? n 2 Cubic ? n 3 In a log-log chart, the slope of the line corresponds to the growth rate of the function. Constant Factors. The growth rate is not affected by constant factors or lower-order terms Examples

683 views • 28 slides

The Sensor Cover Problem

The Sensor Cover Problem. Alon Efrat (U. Arizona) Adam Buchsbaum (AT&T Labs) Shaili Jain (Harvard) Suresh Venkatasubramanian (AT&T Labs) Ke Yi (AT&T Labs). Sensors. Low-power devices with sensing capabilities Sensors monitoring regions

348 views • 28 slides

Pspice(AC SWEEP)

Pspice(AC SWEEP). ????. ????????. ????????. ????. 1 ? Ntype(device): ?????????? type ?????? device ?????? ? :NTOT(R1) ?? R1 ????? (total noise) 2 ????????? : (1) ????????? V(ONOISE) (2) ????????? V(INOISE) (3) ????????? I(INOISE). ??. ??????. ????? :

460 views • 27 slides

Counting Distinct Objects over Sliding Windows

Counting Distinct Objects over Sliding Windows. Presented by: Muhammad Aamir Cheema. Joint work with Wenjie Zhang, Ying Zhang and Xuemin Lin. University of New South Wales, Australia. Introduction. Counting distinct objects: Given a dataset D, return the number of distinct objects in D.

468 views • 27 slides

Class 7.2: Graphical Analysis and Excel

Class 7.2: Graphical Analysis and Excel. Solving Problems Using Graphical Analysis. Learning Objectives. Learn to use tables and graphs as problem solving tools Learn and apply different types of graphs and scales Prepare graphs in Excel Be able to edit graphs

402 views • 26 slides

Fully Homomorphic Encryption

Fully Homomorphic Encryption. Paper by: Craig Gentry Presented By: Daniel Henneberger. What is h omomorphic encryption?. Homomorphic Encryption. Computations on ciphertext which predictably modifies the plaintext Operate on messages while they are encrypted

1.35k views • 25 slides

CSE565: Computer Security Lectures 8, 9 Public Key Cryptography and RSA

376 views • 25 slides

Unit 4 We love animals

401 views • 25 slides

Trigger studies for GMSB with photons (Internal note for approval)

Trigger studies for GMSB with photons (Internal note for approval). Shilei Zang Bernadette Heyburn, Uriel Nauenberg University of Colorado, Boulder. TSG Meeting, 19th Mar. 2008. Outline. GMSB with photons Signal and background samples Efficiency and rate for default triggers

358 views • 25 slides

Analysis Tools

Analysis Tools. Briana Morrison. The Big Idea. How will we compare one data structure with another? How do I know when to use a Red-Black Tree versus a Hash Table?

317 views • 22 slides

Section 5.3 Properties of Logarithms

Section 5.3 Properties of Logarithms. Advanced Algebra. Properties of Logarithms. log b 1 = 0 Anything raised to the 0 power is 1. log b b = 1 Anything raised to the 1st power is that anything log b b x = x Think about as exponent: b x = b x Rewrite as a log: log b x = log b x.

415 views • 18 slides

Lecture 4 : Accelerated Cascading and Parallel List Ranking

Lecture 4 : Accelerated Cascading and Parallel List Ranking. We will first discuss a technique called accelerated cascading for designing very fast parallel algorithms. We will then study a very important technique for ranking the elements of a list in parallel. Fast computation of maximum.

305 views • 16 slides

Dynamic Load Balancing in Distributed Hash Tables

Dynamic Load Balancing in Distributed Hash Tables. Marcin Bie?kowski Miros?aw Korzeniowski Friedhelm Meyer auf der Heide. Ring / Hypercube Topologies. .1. Chord, Tapestry, Pastry, de Bruijn Space: ring [0,1] Arithmetics mod 1 Links to: predecessor and successor shortcuts Degree: log n

288 views • 15 slides

Engr 0012 (04-1) LecNotes 10-01

254 views • 15 slides

7-5 Logarithmic & Exponential Equations

263 views • 10 slides

EXAMPLE 7

log. a. . y. x. =. 3. EXAMPLE 7. Graph logarithmic functions. Graph the function. SOLUTION. Plot several convenient points, such as (1, 0) , (3, 1) , and (9, 2) . The y -axis is a vertical asymptote.

147 views • 6 slides

Solving Lagarithmic Equations

Solving Lagarithmic Equations. Solving Log Equations. We will be using all of the properties. You will have to figure out which ones to use and when to use them. You will have to use other math skills, like factoring, at times.

178 views • 6 slides