Support Vector Machines (Cont..) ‏

Apr 05, 2019

80 likes | 173 Views

Support Vector Machines (Cont..) ‏. Hinge Loss. +. +. +. Penalty. +. -. +. -. +. +. -. -. -. +. -. H. -. -. How far from sep. plane. Recall. PLR. Lins. Dual Representation. Instead of holding . in memory,. Hold. Kernal Function. x. -. -. -. -. -. -. -. -.

Share Presentation

Embed Code

Link

penalty
dual representation
support vector machines
kernal function
hinge loss

clove

Download Presentation

Support Vector Machines (Cont..) ‏

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Support Vector Machines (Cont..)‏
Hinge Loss + + + Penalty + - + - + + - - - + - H - - How far from sep. plane
Recall PLR Lins
Dual Representation Instead of holding in memory, Hold

Kernal Function x
- - - - - - - - - - - - - + + + + + - - - - -

Kernel – Based Methods

Kernel – Based Methods . Presented by Jason Friedman Lena Gorelick. Advanced Topics in Computer and Human Vision Spring 2003. Agenda…. Structural Risk Minimization (SRM) Support Vector Machines (SVM) Feature Space vs. Input Space Kernel PCA Kernel Fisher Discriminate Analysis (KFDA).

1.36k views • 96 slides

14 Vector Autoregressions, Unit Roots, and Cointegration

14 Vector Autoregressions, Unit Roots, and Cointegration. What is in this Chapter?. This chapter discusses work on time-series analysis starting in the 1980s. First there is a discussion of vector autoregression models, Next we talk of the different unit root tests.

1.36k views • 42 slides

Synchronous Machines

Synchronous Machines. Synchronous Machines. Synchronous generators or alternators are used to convert mechanical power derived from steam, gas, or hydraulic-turbine to ac electric power Synchronous generators are the primary source of electrical energy we consume today

1.56k views • 47 slides

VECTOR CALCULUS

16. VECTOR CALCULUS. VECTOR CALCULUS. Here, we define two operations that: Can be performed on vector fields. Play a basic role in the applications of vector calculus to fluid flow, electricity, and magnetism. VECTOR CALCULUS. Each operation resembles differentiation.

1.48k views • 61 slides

Vector Space Text Classification

Vector Space Text Classification. Adapted from Lectures by Raymond Mooney and Barbara Rosario. Text Classification. Today: Introduction to Text Classification K Nearest Neighbors Decision boundaries Vector space classification using centroids Decision Trees (briefly) Later

1.21k views • 69 slides

VECTOR CALCULUS

16. VECTOR CALCULUS. VECTOR CALCULUS. 16.3 Fundamental Theorem for Line Integrals. In this section, we will learn about: The Fundamental Theorem for line integrals and determining conservative vector fields. . FTC2. Equation 1 .

1.24k views • 89 slides

Pipelining and Vector Processing

Pipelining and Vector Processing. Chapter 8 S. Dandamudi. Basic concepts Handling resource conflicts Data hazards Handling branches Performance enhancements Example implementations Pentium PowerPC SPARC MIPS. Vector processors Architecture Advantages Cray X-MP Vector length

1.03k views • 88 slides

SIDEROSIS

SIDEROSIS. Introduction. Siderosis – excessive deposition of iron in body tissue. Organs involved: Spine/ Brains – superficial siderosis . Cont.…. Liver – hepatic siderosis. Cont.…. Eyes – siderosis bulbi. Cont.…. Bladder – urinary siderosis Lungs – ‘respiratory’ siderosis.

1.29k views • 24 slides

Vectors & Relative Motion

Vectors & Relative Motion. Multiple-Choice Practice Problems. Question #1. In a diagram, the length of a vector arrow represents the type of vector. direction of the vector. magnitude of the vector. cause of the vector. . Question #2.

987 views • 23 slides

Kernel – Based Methods

Kernel – Based Methods. Presented by Jason Friedman Lena Gorelick. Advanced Topics in Computer and Human Vision Spring 2003. Agenda…. Structural Risk Minimization (SRM) Support Vector Machines (SVM) Feature Space vs. Input Space Kernel PCA Kernel Fisher Discriminate Analysis (KFDA).

1.13k views • 96 slides

VECTOR CALCULUS

16. VECTOR CALCULUS. VECTOR CALCULUS. So far, we have considered special types of surfaces: Cylinders Quadric surfaces Graphs of functions of two variables Level surfaces of functions of three variables. VECTOR CALCULUS.

1.51k views • 107 slides

Support Vector Machine 支持向量機

Support Vector Machine 支持向量機. Speaker ： Yao-Min Huang Date ： 2004/11/17. Outline. Linear Learning Machines Kernel-Induced Feature Optimization Theory SVM Concept Hyperplane Classifiers Optimal Margin Support Vector Classifiers ν-Soft Margin Support Vector Classifiers

1.23k views • 71 slides

VECTOR CALCULUS

16. VECTOR CALCULUS. VECTOR CALCULUS. 16.2 Line Integrals. In this section, we will learn about: Various aspects of line integrals in planes, space, and vector fields. LINE INTEGRALS.

1.37k views • 107 slides

Cryptography on Non-Trusted Machines

Cryptography on Non-Trusted Machines. Stefan Dziembowski. Idea. Design cryptographic protocols that are secure even on the machines that are not fully trusted. How to construct secure digital systems?. MACHINE (PC, smartcard, etc.). very secure

2.09k views • 175 slides

Chapter 3 Vector Spaces

Chapter 3 Vector Spaces. 3.1 Vectors in R n 3.2 Vector Spaces 3.3 Subspaces of Vector Spaces 3.4 Spanning Sets and Linear Independence 3.5 Basis and Dimension 3.6 Rank of a Matrix and Systems of Linear Equations 3.7 Coordinates and Change of Basis.

3.49k views • 89 slides

Vector Calculus

CHAPTER 9.1 ~ 9.4. Vector Calculus. Contents. 9.1 Vector Functions 9.2 Motion in a Curve 9.3 Curvature and Components of Acceleration 9.4 Partial Derivatives. 9.1 Vector Functions.

1.2k views • 81 slides

Support Vector Machine

Support Vector Machine. Binary Classification Linear Classifiers Rosenblatt Perceptron Maximal Margin Classifier Support Vector Machines References: N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines. Cambridge: Cambridge University Press, 2000.

1.43k views • 76 slides

Support Vector Machines and Radial Basis Function Networks

Support Vector Machines and Radial Basis Function Networks. Instructor: Tai-Yue (Jason) Wang Department of Industrial and Information Management Institute of Information Management. Statistical Learning Theory. Learning from Examples. Learning from examples is natural in human beings

2.16k views • 194 slides

Big Question: How do machines help people work together?

Big Question: How do machines help people work together?. Author: Margaret Mayo Illustrator: Alex Ayliffe Genre: Concept Book. Monday Tuesday Wednesday Thursday Friday Review. Big Question: How do machines help people work together?. Review New Words Progress Monitoring.

2.06k views • 180 slides

Support Vector Machine Classifiers

Support Vector Machine Classifiers. Based on lecture slides by Glenn Fung, O. L. Mangasarian, Rob Lothian, and Kristin Bennett. Outline. Support Vector Machines for Classification Linear Discrimination Nonlinear Discrimination SVM Mathematically Extensions Application in Drug Design

1.2k views • 89 slides

More Related

Support Vector Machines (Cont..) ‏

Support Vector Machines (Cont..) ‏

Presentation Transcript

Kernel – Based Methods

14 Vector Autoregressions, Unit Roots, and Cointegration

Synchronous Machines

VECTOR CALCULUS

Vector Space Text Classification

VECTOR CALCULUS

Pipelining and Vector Processing

SIDEROSIS

Vectors &amp; Relative Motion

Kernel – Based Methods

VECTOR CALCULUS

Support Vector Machine 支持向量機

VECTOR CALCULUS

Cryptography on Non-Trusted Machines

Chapter 3 Vector Spaces

Vector Calculus

Support Vector Machine

Support Vector Machines and Radial Basis Function Networks

Big Question: How do machines help people work together?

Support Vector Machine Classifiers

Vectors & Relative Motion