6 Inference F Now that we have DONE some hypothesis tests... we must sit back and think... so what? What does it all mean?
Scalable Learning and Inference in Hierarchical Models of... Google TechTalks January 17, 2006 Tom Dean ABSTRACT Borrowing insights from computational neuroscience, we present a class of generative models well suited to modeling perceptual processes and an algorithm for learning their parameters that promises to scale to learning very large models. The models are hierarchical, composed of multiple levels, and allow input only at the lowest level, the base of the hierarchy. Connections within a level are generally local and may or may not be directed. Connections between levels are directed and generally do not span multiple levels. The learning algorithm falls within the general family of expectation maximization algorithms. Parameter estimation...
Observation vs. Inference Explaining the difference between observations and inferences through a discrepant event.
Inference Inference Song
Making Inferences Third grade students from Mr. Salsich's class ( at Deans Mill School explain how to make inferences while reading.
Inferences: Knowing text structure Use inferencing skills to help figure out the progression of ideas and text structure of a narrative. Inference, cause and effect, chronological order, compare and contrast. This skill is under Objective 3 for the Taks.
Inference for .NET 3 Minute Overview - use IronPython or IronRuby in Microsoft Office 3-minute overview of Inference for .NET. Use IronPython and IronRuby .NET languages to develop, document, and publish in Microsoft Excel and Word. Visit to download a free 30-day trial or to request a free academic license.
Inference Track 4 Track 4 :)
SAT & ACT Reading: Making Inferences Learn SAT and ACT test strategies about how to answer questions that ask you to infer the answer based on a reading passage by predicting an answer and looking for support in the passage.
inference The logical process of inference
What's The Inference? Nothing inferred by the statement before the rap. I'm jewish errrybody! Debut album drops June 2011 - 7 Years In Isolation /atrophyone /xxatrophyxx for more info, and music.
6 Inference C.avi The epistemology of inference: That is, what can we learn about the world from collecting data and how do we know it?
Inference for Matlab 2 Minute Overview A brief overview of Inference for MATLAB - integrating the technical computing of MATLAB with the power and flexibility of Microsoft Office. Visit www.InferenceForMATLAB to view a free 30-day trial or apply for a free year-long academic license. Using Inference for MATLAB, you can - Execute MATLAB code directly inside Microsoft Word to create formatted reports that contain explanatory text and graphical/code output. - Execute MATLAB code directly inside Microsoft Excel to create dynamic spreadsheets that leverage existing Excel functionality. - Store all your MATLAB code, data, and M-Files inside a single Microsoft Word and Excel document.
SILICON VALLEY: LOGICAL POSITIVISM, MATHS, PROBABILITY, INFERENCE Chris Horrie interviews Professor Keith Devlin as part of the History and Context of Journalism series at the University of Winchester. Professor Devlin is a co-founder and Executive Director of the university's H-STAR institute, a co-founder of the Stanford Media X research network, and a Senior Researcher at CSLI. He is a World Economic Forum Fellow and a Fellow of the American Association for the Advancement of Science. His current research is focused on the use of different media to teach and communicate mathematics to diverse audiences. He also works on the design of information/reasoning systems for intelligence ***ysis. Other research interests include: theory of information, models of reasoning, applications of mathematical techniques in the study of communication, and mathematical cognition. He has written 28 books and over 80 published research articles. Recipient of the Pythagoras Prize, the Peano Prize, the Carl Sagan Award, and the Joint Policy Board for Mathematics Communications Award. In 2003, he was recognized by the California State Assembly for his "innovative work and longtime service in the field of mathematics and its relation to logic and linguistics." Here he was interviewed by Chris Horrie during the Innovation Journalism conference at Stanford University in Silicon Valley, California. Professor Devlin deals with important concepts underlying the History and Context of Journalism course at the University of Winchester including the basics of ...
RUU #19: Inference on the free binomial model In this clip, I study inference on the free binomial model. Recall that the binomial distribution gives the probability for a given number of successes,k, for a given number, n, of repeatable independent trials. A fixed success probability, p, is assumed (hence repeatable trials). The object is to gather info on the value of p, and handle that info using Bayes formula, since it will typically be a' priori uncertain. The example is from a game called Age of Wonders (Shadow Magic), which I warmly recommend, by the way. (It's an excellent time waster :) I'm studying the probability for a knight winning over a dragon, by doing 100 separate «battles». The result is 9 surviving knights. I then study that data using probabilistic theory. The results include the posterior probability of p (the probability of p given the data), estimates of p, the standard deviation of p, a 90% credibility interval for p (an interval of p where more than 90% of the probability is situated) and predictions of future events based on the posterior distribution. The slides can be found here: folk.uio.no R code for doing the inference can be found here: folk.uio.no The statistical programming tool R can be downloaded freely, here: www.r-
Lecture 5 -Logical Inference Discrete Mathematical Structures -Logical Inference
Embedded Image Processing - Color Segmentation using Fuzzy Inference System OpenCV library built for an embedded processor (i.MX51 - ARM Cortex A8) This program performs color segmentation on frames grabbed from an USB Camera (webcam) in real time. It uses Ubuntu Linux as Operating System and the board used was the EVK board from Freescale Semiconductors (Freescale's i.MX51 processor): the process used to perform this operation was: 0 - Re-scaling (the input image was downsized) 1 - Color System Conversion RGB to HSV 2 - Color filter (thresholds on both HUE and SAT planes for the first result and Fuzzy for the second) 3 - Color System Conversion HSV to RGB 4 - Color Conversion RGB to Grayscale 5 - Smooth with Gaussian filter 5x5 in order to get a complete operation, mathematical morphology (erode and dilate) and also binarization (after smoothing) are needed in this case. the System's clock speed is 800Mhz with 512MB of RAM memory, and with all those steps above the detection time is only 1,3ms per frame. Fuzzy Inference System information: Discretization Points: 20 Inference Rules: 3 for each color Implication Method: Mandani Defuzzyfication Method: Largest of Maximum (LOM)
Inference in Practice Describes when inference and significance tests are to be used and the basic cautions when evaluating the results of tests of significance.
Does Googlebot use inference when crawling? Leon from the UK asks: "Does GoogleBot use inference when spidering - having crawled /article/page1.htm and /page2.htm, can it guess at the existence of a /page3.htm and crawl it? Or does it stick entirely to what it finds via the link graph and/or Sitemaps/feeds?" Thisvideo is part of a "Grab Bag" series in which Matt Cutts, head of Google's webspam team, answers questions from webmasters. We're not currently taking new video questions, so your best bet for getting an answer about webmaster-related search issues is to head to our help forum:
Criminal Minds 5x12: Reid's Inference CM 5x12 "Uncanny Valley" The BAU is called to Atlantic City to profile a suspect with an unusual personal obsession who is abducting and killing certain a certain type of woman.
QI - The Farminator Small clip from the the Series F, Episode 6 of QI ("France"), describing what happened when Arnold Schwarzenegger requested to dub "The Terminator" for the German release of the film. Copyright the BBC
Fermat number inference - 2/2 Re:Stanford Challenge In this two-part set of clips, I take a look at a particular inference on the so-called Fermat numbers. These numbers were inferred to be only prime numbers, but that later turned out to be false. I show how to tackle this problem using statistical tools, in order to see exactly how much you would trust the inference in this case. I do not elaborate too much on the statistical methods, so this can be seen more as a demo than anything else. In this second clip, I study the Bayesian approach. I start off with a numeric experiment to determine the a' priori' probability that an arbitrary sequence produces only prime numbers. I use conservative estimate of 10% which produces an a' posteriori (after data) probability of 94%, with a 6% chance of being wrong. I then try a more sophisticated method, using a probability distribution for the prior probability, yielding a mean posterior probability of 19% for being wrong in the inference. Thus, the ***ysis shows that even though the data indicates that the sequence contains only prime numbers, we can not put a lot of trust in that assumption. When the next part of the sequence arrives, the probability for the sequence being only prime collapses to zero. Some useful wikipedia links: (Tells how to deduce Bayes theorem from the rules of probability) (Contains a description of probability distributions on probabilities!) Intro to Bayesian statistics with comparisons between Bayesian and frequentist ...
Ladder Of Inference part 2 Continuation of Part 1.
Google SketchUp Technique Series: Inference Locking Inference locking is the ability to draw or move in only one locked direction in SketchUp. This video will teach you how to use this technique and show a few examples of inference locking in use.
Ladder Of Inference part 1 Ray Jorgensen, Ph.D illustrates to the Florida City and County Management Association (FCCMA) how we jump to conclusions and that doing so can damage relationships and ultimately shut down communication in the organization.
Lecture - 10 Inference in First Order Logic Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, IIT,kharagpur. For More details on NPTEL visit nptel.iitm.ac.in
Inference in Excel and Word Overview - write R code in Microsoft Office An overview of the features and capabilities of Inference for R and combining the power of R scripting with Microsoft Office. This screencast focuses on using Inference in Excel and Inference in Word. Visit to download a free 30-day trial, or to request a free academic license.
Lambda calculus with type inference in Eastwest A full implementation of lambda calculus with type inference in Eastwest.
The Design Inference: A Response to WL Craig (Part 2) I continue to hand William Lane Craig his own ass as I pick apart this video:
Statistical Inference The meaning and purpose of statistical inference and the tools that statisticians have created in order to enable you to estimate how close and with what confidence you can draw conclusions about a population on the basis of a sample drawn from that population.
Web-based Inference Detection Google Tech Talk February 13, 2009 ABSTRACT Presented by Jessica Staddon. Text content can allow unintended inferences. Consider, for example, the numerous people who have published anonymous blogs for venting about their employer only to be identified through seemingly non-identifying posts. Similarly, the US government's "Operation Iraqi Freedom Portal" was assembled as evidence of nuclear weapons presence in Iraq, but removed because it could be used to infer much of the weapon making process. We propose a simple, semi-automated approach to detecting text-based inferences prior to the release of content. Our approach uses association rule mining of the Web to identify keywords that may allow a sensitive topic to be inferred. While the main application of this work is data leak prevention we will also discuss how it might be used to detect bias in product reviews. Finally, if time permits, we will discuss how inference detection can support topic-driven access control. Most of this talk is joint work with Richard Chow and Philippe Golle. Jessica is an area manager at PARC (aka Xerox PARC). She received her PhD in Math from UC Berkeley and has held research scientist positions at RSA Labs and Bell Labs. Jessica's background is in applied cryptography, specifically, cryptographic protocols for large, dynamic groups. Her current research interests include the use of data mining to support content privacy.
Information Extraction, Data Mining and Joint Inference Andrew McCallum, Computer Science, U. Massachusetts Amherst, MA This lecture has been videocast from the Computer Science Department at Duke. The abstract of this lecture and a brief speaker biography is available at: research.csc.ncsu.edu
Local Type Inference Visual Basic and C# now provide a feature that lets you write code without specifying the types of local variables. The compilers can infer the type that is needed based on the surrounding code.
6 Inference H.avi Discover Your Inner Alpha: Why do people talk about alpha=.05 in hypothesis testing? Why do some people use .10 or .01? Discover your inner alpha in this experiment, your willingness to commit a type 1 error.
Learning and Inference for Hierarchically Split PCFGs Google Tech Talks February, 28 2008 ABSTRACT Treebank parsing can be seen as the search for an optimally refined grammar consistent with a coarse training treebank. We describe a method in which a minimal grammar is hierarchically refined using EM to give accurate, compact grammars. The resulting grammars are extremely compact compared to other high-performance parsers, yet the parser gives the best published accuracies on several languages, as well as the best generative parsing numbers in English. In addition, we give an associated coarse-to-fine inference scheme which vastly improves inference time with no loss in test set accuracy. Slides: www.eecs.berkeley.edu Speaker: Slav Petrov Slav Petrov is a Ph.D. Candidate at University of California Berkeley Dept of Computer Science, where he is also a research assistant working with Dan Klein and Jitendra Malik on inducing latent structure for perception problems in vision and language.
Fermat number inference - 1/2 Re:Stanford Challenge websnarf In this two-part set of clips, I take a look at a particular inference on the so-called Fermat numbers. These numbers were inferred to be only prime numbers, but that later turned out to be false. I show how to tackle this problem using statistical tools, in order to see exactly how much you would trust the inference in this case. I do not elaborate too much on the statistical methods, so this can be seen more as a demo than anything else. In the first clip, I do a little intro and then start off with frequentist hypothesis-testing. That goes a bit awry, which is precisely what I want to demonstrate here, though a more thorough treatment may yield better results. If this is a little un-satisfying, you can fast-forward to the end, where I introduce Bayesian statistics. The number of primes below specified thresholds can be found here: primes.utm.edu For more on p-values, see
6 Inference E.avi Statistical Inference: Actually Doing it, Part 2. An introduction to the p-value.
ICDE 2008 DBClip: Inference Engine for RDFS/OWL A summary of the "Implementing an Inference Engine for RDFS/OWL Constructs and User-Defined Rules in Oracle" paper from Oracle to be presented at the ICDE 2008 Conference in Cancun Mexico.
Inference for R (the premier IDE for R) 3-Minute Overview A brief overview of the Inference for R development environment, primarily focusing on Inference Studio, the premier IDE for R. Download a free trial of Inference for R at . Optimize your R development experience.
Max-margin training and inference on structured models for information extrac... Google Tech Talks June, 2 2008 ABSTRACT Feature-based structured models provide a flexible and elegant framework for various information extraction (IE) tasks. These include label sequences for traditional IE, segmentation models for entity-level extractions, and skip chain models for collective labeling. I will present efficient inference algorithms for finding the highest scoring (MAP) prediction for two interesting types of structured models in IE. I will then present our recent results in max-margin training of such models. There are two popular formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling is extremely popular since it requires the same kind of MAP inference as prediction, slack scaling is believed to be more accurate and better-behaved. I will describe an efficient variational approximation to the slack scaling method that solves its inference bottleneck while retaining its accuracy advantage over margin scaling. Further I argue that existing scaling approaches do not separate the true labeling comprehensively while generating violating constraints. I will propose a new max-margin trainer PosLearn that generates violators to ensure separation at each position of a decomposable loss function. Speaker: Sunita Sarawagi Sunita Sarawagi researches in the fields of databases, data mining, machine learning and statistics. Her current research interests are information integration, graphical and ...
Google SketchUp Technique Series: Inference Locking Example Download at As a follow-up video to inference locking, this video shows how to combine a series of roof forms together using inference locking. Please keep in mind, this isn't a video on roofs, but an example of various inference locking techniques.
Rock Band Network (Audition) Expert Drums The Inference by Go Mordecai (Autoplay) Another Song by request. Nothing fast, nothing pretty hard and short. As uploading the full file is illegal, you only can download the midi file here: Sync it with the song in Reaper and you are ready to go!