PPT-Randomized Algorithms

CS648 Lecture 6 Reviewing the last 3 lectures Application of Fingerprinting Techniques 1dimensional Pattern matching Preparation for the next lecture 1 Randomized Algorithms discussed till now. Impact Evaluation Methods for Policy Makers. This material constitutes supporting material for the "Impact Evaluation in Practice" book. This additional material is made freely but please acknowledge its use as follows: . Adversarial Environments. Andreas . Krause. Joint work with . Daniel . Golovin. and . Alex Roper. International Joint Conference on Artificial Intelligence 2011. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . CS648. . Lecture 15. Randomized Incremental Construction . (building the background). 1. Partition Theorem. A set of events . ,…,. . defined over a probability space (. ,. P. ) is said to induce a partition of . Michael Ben-Or. The Hebrew University. Michael Rabin’s Birthday Celebration. Randomized Protocols. Power of Randomization. Exponential . speedup for known algorithms. Complexity . – The jury is still out . 1. , Dragi Kocev. 2. , . Suzana Lo. skovska. 1. , . Sašo Džeroski. 2. 1. Faculty of Electrical Engineering and Information Technologies, Department of Computer Science, Skopje, Macedonia. . 2. . Complexity of Voting Manipulation Revisited . b. ased on joint work with . Svetlana . Obraztsova. . (NTU/PDMI). and. . Noam . Hazon. . (CMU). Edith Elkind. . (Nanyang. Technological University, Singapore. of a graph. Spyros Angelopoulos*. Christoph . Dürr. *. Thomas . Lidbetter**. *. Sorbonne Universités. , UPMC . Univ. Paris 06, CNRS, LIP6, Paris, . France. **Department of Mathematics, London School of Economics, . Data Collection: . Experiments and Observational Studies. 1/23/12. Association. versus Causation. Confounding Variables. Observational Studies . vs. Experiments. Randomized Experiments. Section 1.3. This material constitutes supporting material for the "Impact Evaluation in Practice" book. This additional material is made freely but please acknowledge its use as follows: . Gertler. , P. J.; Martinez, S., . . Lecture 2. Randomized Algorithm for Approximate Median. Elementary Probability theory. 1. Randomized Monte Carlo . Algorithm for. . approximate median . 2. This lecture was delivered at slow pace and its flavor was that of a tutorial. . Lower Bounds, and Pseudorandomness. Igor Carboni Oliveira. University of Oxford. Joint work with . Rahul Santhanam. (Oxford). 2. Minor algorithmic improvements imply lower bounds (Williams, 2010).. NEXP. What is an Experiment?. Campbell & Stanley stressed random assignment to experimental treatments.. I stress manipulation of the independent variable.. Quasi-Experiments: C&S’s term for research where. Problem - a well defined task.. Sort a list of numbers.. Find a particular item in a list.. Find a winning chess move.. Algorithms. A series of precise steps, known to stop eventually, that solve a problem.. PROOF IN MEDICAL RESEARCH. Susan S. . Ellenberg. , Ph.D.. Department of Biostatistics and Epidemiology. Perelman School of Medicine, U Penn. Statistics is the science of uncertainty. Biostatistics is the application of statistics to biological problems.