PPT-Adapting to Adaptivity Transformations

in Teaching and Learning Southeast Digital Learning Forum UNC Charlotte February 2019 Dale P Johnson Director Adaptive Learning Initiatives The future is already here its just not evenly distributed. a 12 22 a a mn is an arbitrary matrix Rescaling The simplest types of linear transformations are rescaling maps Consider the map on corresponding to the matrix 2 0 0 3 That is 7 2 0 0 3 00 brPage 2br Shears The next simplest type of linear transfo vanetS. Irem Nizamoglu. Computer Science & Engineering. Outline. Motivation. Epidemic Protocols. EpiDOL. Parameter Optimization. Performance Results & . Adaptivity. Features. Conclusion. Outline. Mark . Goffin - . EngD. . Research . Engineer. Christopher Baker – . EngD. Research Engineer. Dr Andrew Buchan. Dr Matthew Eaton. Prof. Chris Pain. Contents. Introduction. RADIANT. Spatial . discretisation . Ch. 2 Lesson 3. Pg. 123. What will you will learn?. Enlarge Photographs. Make something from a pattern. Identify Similarity. Two figures are . similar. if the second can be obtained from the first by a sequence of transformations and dilations. WHAT IS IT?. Preparing and modifying primary source documents so that all students can read and analyze them in their history classrooms.. Adapting Documents. RATIONALE. Often primary sources use complex or antiquated language. Lecture 3. Jitendra. Malik. Pose and Shape. Rotations and reflections are examples. of orthogonal transformations . Rigid body motions. (Euclidean transformations / . isometries. ). Theorem:. Any rigid body motion can be expressed as an orthogonal transformation followed by a translation.. Maurice J. . Chacron. and Kathleen E. Cullen. Outline. Lecture 1: . - Introduction to sensorimotor . . transformations. - . The case of “linear” sensorimotor . transformations: . Gaps for stochastic . probing. (Submodular . & XOS . Functions). Sahil. . singla. . Carnegie . mellon. university. Joint work with . Anupam. . gupta. . and. . viswanath. . nagarajan. 18. th. Sahil. . singla. . Joint work with . Anupam. . gupta. . and. . viswanath. . nagarajan. (2. nd. December, 2015). Stochastic probing. 2. Only 1 hour before shops close!. Orienteering Constraint. Learning Targets: 8.G.2,8.G.3, 8.G.4. Follow the slides to learn more about transformations. Students should have paper and a pencil for notes at their desk while going through this presentation.. Transformation: a transformation is a change in position, shape or size.. Anupam Gupta. Carnegie Mellon University. SODA . 2018, New Orleans. stochastic optimization. Question. : . How to . model and solve problems with . uncertainty in . input/actions?. data . not . yet . CS5670: Computer Vision. Reading. Szeliski. : Chapter 3.6. Announcements. Project 2 out, due Thursday, March 3 by 8pm. Do be done in groups of 2 – if you need help finding a partner, try Ed Discussions or let us know. February 2019. Paola Davis. GDPR and events. Ensuring delegates give the right consents. Updating privacy policy. Promotion of events – updating mailing lists. Exhibition and sponsorships – how our partners behave with data. Dr. Karen/Pinky Schultz. On Behalf of the CFPC Certification Process and Assessment Committee. FMF Montreal 2023. Faculty/Presenter Disclosure. Disclosure of Financial Support. Objectives -- At the end of this session, participants will be able to:.