'Proof sketch' presentation slideshows

Propagation on Large Networks

955 views • 87 slides

Discrete Optimization Lecture 2

858 views • 69 slides

Direct Product : Decoding & Testing

620 views • 52 slides

[Paper Survey] Profinite Methods in Automata Theory

514 views • 42 slides

Some Fundamentals of Stability Theory

Some Fundamentals of Stability Theory. Aaron Greenfield. Outline. Introduction + Motivation Definitions Theorems Techniques for Lyapunov Function Construction. Basic Notion of Stability. Stability. An important property of dynamic systems. Stability. . .

1.22k views • 39 slides

NP-complete examples

NP-complete examples. CSCI3130 Tutorial 10. Chun-Ho Hung. chhung@cse.cuhk.edu.hk. Department of Computer Science & Engineering. Outline. Review P, NP, NPC Polynomial-time Reduction 2 problem s Double-SAT Dominating set http://en.wikipedia.org/wiki/Dominating_set_problem. Review.

511 views • 39 slides

Direct-product testing, and a new 2-query PCP

489 views • 38 slides

exercise in the previous class (1)

527 views • 33 slides

CS621: Artificial Intelligence

402 views • 29 slides

Algorithmic and Economic Aspects of Networks

Algorithmic and Economic Aspects of Networks. Nicole Immorlica. Random Graphs. What is a random graph?. Erdos-Renyi Random Graphs. Specify number of vertices n edge probability p For each pair of vertices i < j, create edge (i,j) w/prob. p. G(n,p). Erdos-Renyi Random Graphs.

433 views • 28 slides

Sequential Hypothesis Testing under Stochastic Deadlines

Sequential Hypothesis Testing under Stochastic Deadlines. Peter Frazier, Angela Yu Princeton University. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A A A. Sequential Hypothesis Testing. under Stochastic Deadlines .

460 views • 27 slides

Latent Semantic Indexing: A probabilistic Analysis

Latent Semantic Indexing: A probabilistic Analysis. Christos Papadimitriou Prabhakar Raghavan, Hisao Tamaki, Santosh Vempala. Motivation . Application in several areas: querying clustering, identifying topics Other: synonym recognition (TOEFL..) Psychology test essay scoring. Motivation.

368 views • 24 slides

Online Passive-Aggressive Algorithms

Online Passive-Aggressive Algorithms. Shai Shalev-Shwartz joint work with Koby Crammer, Ofer Dekel & Yoram Singer The Hebrew University Jerusalem, Israel. Three Decision Problems. Classification. Regression. Uniclass. Online Setting. Classification Regression Uniclass.

831 views • 21 slides

Decidable Containment of Recursive Queries

Decidable Containment of Recursive Queries. Diego Calvanese, Giuseppe De Giacomo, Moshe Y. Vardi presented by Axel Polleres http://www.dis.uniroma1.it/pub/calvanes/calv-degi-vard-ICDT-2003.pdf. Query Containment.

486 views • 17 slides

Codes for Deletion and Insertion Channels with Segmented Errors

Codes for Deletion and Insertion Channels with Segmented Errors. Zhenming Liu Michael Mitzenmacher Harvard University, School of Engineering and Applied Sciences. The Most Basic Channels. Binary erasure channel. Each bit is replaced by a ? with probability p . Binary symmetric channel.

385 views • 17 slides

Chapter 21

Chapter 21. Asynchronous Network Computing with Process Failures By Sindhu Karthikeyan. 21.1 The Network Model

324 views • 17 slides

6.853: Topics in Algorithmic Game Theory

6.853: Topics in Algorithmic Game Theory. Lecture 16. Fall 2011. Constantinos Daskalakis. Recap. Exchange Market Model. traders. divisible goods. trader i has:. - utility function. non-negative reals. consumption set for trader i.

308 views • 17 slides

Learning with Similarity Functions

Learning with Similarity Functions. Maria-Florina Balcan & Avrim Blum CMU, CSD. Kernels and Similarity Functions. Kernels have become a powerful tool in ML. Useful in practice for dealing with many different kinds of data.

364 views • 16 slides

Lecture 7 CS 728

Lecture 7 CS 728. Searchable Networks. Errata: Differences between Copying and Preferential Attachment. In generative model: let p k be fraction of nodes with (in)degree k Consider the degree distribution of attaching new node to target of randomly chosen edge.

219 views • 10 slides