Genetic Algorithm Fish evolution of fish. each fish is a neural net. The purpose of this application is to develop a "killer fish" - a fish that eats maximum pieces of food in a constant time period. The world is populated by 20 fish and 40 pieces of food. every time a generation begins. the food is scatted in a random distribution on a certain random location on the screen. (random piles of food). When being eaten, the food shows up in a new random pile in the screen. Every fish has a brain - Neural Net. It has 2 inputs the direction and velocity of the fish. (himself). the relative location of the closest food. and two outputs: velocity of right wheel. velocity of left wheel. You can refer to the movement as a tank with two chains, and the output as the velocity of each chain. the target is to find weights for the neural net that will give the fish a "killer-brain"... When running the application you will see the generations go by. In each generation we select the best fish in generation and breed them to form new 20 fish. the brains (Neural Nets) of the initial 20 fish are created randomly. This explains why they are so "stupid". look how they improve as time goes by. their logic is being build by evolution, without interference.
Algorithms #2 - Insertion Sort We continue looking at sorting algorithms, this time we take a look at Insertion Sort. Insertion is better than bubble sort, but still very poorly behaving.
Algorithms Lesson 1: Bubblesort For this lesson, we demonstrate graphically how to perform the bubblesort algorithm and ***yze its time complexity. For C++ bubble sort code, go to our website . Please direct all questions to our forum:
Lec 1 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 Lecture 01: Administrivia | Introduction | ***ysis of Algorithms, Insertion Sort, Mergesort View the complete course at: ocw.mit.edu License: Creative Commons BY-NC-SA More information at ocw.mit.edu More courses at ocw.mit.edu
Pulmonary Embolus Algorithm This video explains the complete workup, and management of Pulmonary Embolus. This was done with a lot of research, and is an often times disputed topic, so please comment if you have any problems with the information. ENJOY!!
USMLE ALGORITHMS: Cushing Syndrome This video explains the complete workup of Cushing Syndrome, the causes, the diagnosis, and the full management. It is very thorough. I hope you enjoy
Lecture 1: Introduction to Data Structures and Algorithms - Richard Buckland A selection of the course material is available at wiki.cse.unsw.edu.au This is the first lecture of COMP1927 Algorithms and Data Structures, which is the second computing course taken by first year computing students at UNSW. This course follows immediately on from COMP1917 (also available on youtube). These lectures are currently being recorded (August-November 2009).
Lec 3 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 Lecture 03: Divide-and-Conquer: Strassen, Fibonacci, Polynomial Multiplication View the complete course at: ocw.mit.edu License: Creative Commons BY-NC-SA More information at ocw.mit.edu More courses at ocw.mit.edu
Bubble sort algorithm Bubble sorting a list of 5 numbers.
Forest-based Search Algorithms in Parsing and Machine Translation Google Tech Talks March, 14 2008 ABSTRACT Many problems in Natural Language Processing (NLP) involves an efficient search for the best derivation over (exponentially) many candidates, especially in parsing and machine translation. In these cases, the concept of "packed forest" provides a compact representation of the huge search spaces, where efficient inference algorithms based on Dynamic Programming (DP) are possible. In this talk we address two important open problems within this framework: exact k-best inference which is often used in NLP pipelines such as parse reranking and MT rescoring, and approximate inference when the search space is too big for exact search. We first present a series of fast and exact k-best algorithms on forests, which are orders of magnitudes faster than previously used methods on state-of-the-art parsers such as Collins (1999). We then extend these algorithms for approximate search when the forests are too big for exact inference. We discuss two particular instances of this new method, forest rescoring for MT decoding with integrated language models, and forest reranking for discriminative parsing. In the former, our methods perform orders of magnitudes faster than conventional beam search on both state-of-the-art phrase-based and syntax-based systems, with the same level of search error or translation quality. In the latter, faster search also leads to better learning, where our approximate decoding makes whole-Treebank discriminative ...
What different sorting algorithms sound like This particular audibilization is just one of many ways to generate sound from running sorting algorithms. Here on every comparison of two numbers (elements) I play (mixing) sin waves with frequencies modulated by values of these numbers. There are quite a few parameters that may drastically change resulting sound - I just chose parameteres that imo felt best. After making this video I found that someone already tried to audibilize sorting algorithms: - he mentions other older attempt: www.math.ucla.edu And someone in comments metions similar attempt on different aproches to Towers of Hanoi problem in 1982; there was also attempt on trying to hear minimax search in chess engine in 2009: . This is my first attempt on making algorithms audible. For some time I was wondering what would it sound like if cpu made different noises for different instructions. It all started while trying to play raw files (texts, images, programs...), then I heard few "raw" tracks on Alva Noto CD... and then I did one strange audio-visual simulation and then I tried to play out voltage potentials simulated by spiking neural network implementation - it worked out really cool so I wanted to try something with algorithms - thats how I got here. I know this work is not novel but I feel it isn't explored enough. I see future uses of similar techniques in monitoring and debuging, teaching and gaining insight of more complicated algorithms, science (as an ...
USMLE ALGORITHMS: Tuberculosis This discussion is about Tuberculosis and topics covered are the following: -Symptoms -Diagnostic Tests -Disseminated Disease -Therapy and Side effects of therapy -Screening This video tutorial clip continues the series of USMLE ALGORITHMS. Look out for book to be released late Spring. ENJOY!!
Algorithms Lesson 3: Merge Sort For this lesson, we explain and demonstrate graphically how to perform the merge sort algorithm with a pseudocode implementation. For C++ merge sort code, go to our lesson page at . Please submit all questions to our forum:
Algorithms for Data Management and Migration Google Tech Talks January, 23 2008 ABSTRACT I will describe some algorithms for addressing some fundamental optimization problems that arise in the context of data storage and management. In the first part of the talk we will address the following question: How should we store data in order to effectively cope with non-uniform demand for data? How many copies of popular data objects do we need? Where should we store them for effective load balancing? In the second part of the talk we will address the issue of moving data objects quickly, to react to changing demand patterns. We will develop approximation algorithms for these problems. The first part of the talk is joint work with Golubchik, Khanna,Thurimella and Zhu. The second part is joint work with Kim and Wan. Speaker: Samir Khuller Samir Khuller received his MS and Ph.D from Cornell University in 1989 and 1990, respectively. He spent 2 years as a Research Associate at the Institute for Advanced Computer Studies at the University of Maryland, before joining the Computer Science Department in 1992, where he is a Professor and Associate Chair in the Department of Computer Science. His research interests are in graph algorithms, discrete optimization, and computational geometry. He has published about 130 journal and conference papers, and several book chapters on these topics. He received the National Science Foundation's Career Development Award, the Dean's Teaching Excellence Award and also a CTE-Lilly Teaching ...
Binaural Beats, The Sacred Solfeggio, and The Algorithms of Organic Life Systems (HD) We encourage everyone to make a commitment to spend one full day without any electronics on them or nearby. Leave your house, turn off your cell phones, leave your wris***ches at home, and take a walk in a park with your shoes and socks off. Allow yourself to experience pure sound. Take a deep breath and listen... Please Help Ezra and I Raise Funds to Press the First ever Synchromusicology Full Length Double Disk DVD! Donate at ~ To help this research evolve. Thanks ~ S. Willner The TRUE Shape of Sound (It's a Spherical Hologram!) Cymatic glyphs generated by Flutes, Human Voice, Didgeridoo, and Cello: Dolphins playing with rings of bubble-light in water: Redice Creations Special on Solfeggio Frequencies: Brain entrainment + ET = Brain Entertainment: Stanford University Thesis on Binaural Sound and Brain Entrainment: www.stanford.edu Free Isochronous Tones for your Healing: iso- Dr Masaru Emoto Water Research: www.life- Dorothy Retallack's Sound of Music and Plants: Audio Illusions - Holophonic Sound (Free Sound Examples): The best day ever, Mystery, Bubbles, Organic, Sacred, Beats, Rhythm, Harmony, Melody, Music Theory, Philosophy, Anthroposophy, Steiner, Harmonic Ratio, ear, beauty, meditation, truth, Urham, air, elements, tonality ...
Sorting Algorithms - English This is a demonstration of an activity from the Computer Science Unplugged collection of games and activities that demonstrate Computer Science without using computers. For more information, see the activity called "Lightest and Heaviest — Sorting Algorithms" at
CGAL: The Open Source Computational Geometry Algorithms Library Google Tech Talks March, 3 2008 ABSTRACT Introduction Project mission statement, history, internal organization, partners, CGAL in numbers. What's in CGAL A survey on available data structures and algorithms, as well as examples how and by whom they are used. Topics include Triangulations, Voronoi diagrams, Boolean operations on polygons and polyhedra, arrangements of curves and their applications, Mesh generation, Geometry processing, Alpha shapes, Convex hull algorithms, Operations on polygons, Search structures, Interpolation, Shape ***ysis, fitting, and distances, Kinetic data structures... Generic Programming Paradigm CGAL data structures are C++ template classes and functions, usually taking several template parameters (with default values for ease of use). This gives developers an incredible flexibility to adapt the data structures to their needs, which is important internally for code reuse, and important for end users, as they typically integrate CGAL in already existing applications. Parts of CGAL are also interfaced with languages and software like Python, Java, Scilab, Qt and the Ipe drawing editor. Exact Geometric Computing Paradigm We present how to make geometric algorithms correct, robust, and nevertheless fast, by combining floating point arithmetic with exact arithmetic, and clever filtering mechanisms to switch between these two modes. These mechanisms can be used for geometric predicates, as well as for geometric constructions, which instead of a ...
How many search algorithm changes were made in 2009? Pulkit Agrawal in Ahmedabad, India asks: "Can you please tell us: a) How many changes did Google make to their primary search algorithm in 2009 till date? b) Is content still the king or something else (structure) has taken over? This is some big buzz in the Internet community."
Sounding the Stars with Genetic Algorithms Google Tech Talks January 13, 2009 ABSTRACT In February 2009 NASA will launch the Kepler satellite, a mission designed to discover habitable Earth-like planets around distant Sun-like stars. The method that Kepler will use to detect distant worlds will only reveal the size of the planet relative to the size of the host star, so part of the mission is devoted to characterizing distant Suns using a technique known as "asteroseismology". I have developed an automated approach to matching computer models of stars to such observations, based primarily on a parallel genetic algorithm. I will give a broad overview of how we can probe the insides of stars using seismology, and I will provide a general background on the operation of our model-fitting application. I will conclude with our first results on a nearby star: the Sun. Speaker: Travis Metcalfe Travis Metcalfe is an astronomer at the National Center for Atmospheric Research in Boulder, Colorado. He started his career in the backyard of his childhood home in rural Oregon, and continued it in such places as Tucson, Austin, and Boston before landing in Boulder four years ago.
Algorithms Lesson 6: Big O, Big Omega, and Big Theta Notation For this algorithms video lesson, we explain and demonstrate the main asymptotic bounds associated with measuring algorithm performance: big O, big omega, and big theta. in algorithm ***ysis, we are more with how an algorithm scales than the exact time of execution. This is sometimes referred to as complexity ***ysis. Lesson page: Please submit all questions to our forum:
CS 61B Lecture 20: Algorithm ***ysis CS61B: Data Structures - Fall 2006 Instructor Jonathan Shewchuk Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language. www.cs.berkeley.edu
USMLE ALGORITHMS: DIABETES MELLITUS Type 1 and 2 This video clip is going to discuss Diabetes Type 1, and Type 2: -The diagnosis, symptoms, management, complications, and management of complications Topics that will be covered: -Symptomology -Diagnosis -Treatment -Long term Management of Disease -Complications and Management of Complications: - DKA - HONK -CCS Hits for DKA
The Maggie Sort Algorithm My 19 month old daughter researches sorting algorithms. The recursion appears to have dependence on a isNextLargest() function.
Lecture -5 Algorithm Design Techniques : Basics Lecture Series on Design & ***ysis of Algorithms by Prof.Sunder Vishwanathan, Department of Computer Science Engineering,IIT Bombay. For more details on NPTEL visit nptel.iitm.ac.in
Lecture - 3 Algorithms ***ysis Framework - II Lecture Series on Design & ***ysis of Algorithms by Prof.Abhiram Ranade, Department of Computer Science Engineering,IIT Bombay. For more details on NPTEL visit nptel.iitm.ac.in
Algorithms Lesson 2: Insertion Sort For this lesson, we explain and demonstrate graphically how to perform the insertion sort algorithm. For C++ insertion sort code, go to our lesson page at . Please submit all questions to our forum:
Adaptive Algorithms for Online Optimization Google Tech Talks March, 14 2008 ABSTRACT The online learning framework captures a wide variety of learning problems. The setting is as follows - in each round, we have to choose a point from some fixed convex domain. Then, we are presented a convex loss function, according to which we incur a loss. The loss over T rounds is simply the sum of all the losses. The aim of most online learning algorithm is to minimize *regret* : the difference of the algorithm's loss and the loss of the best fixed decision in hindsight. Unfortunately, in situations where the loss function may vary a lot, the regret is not a good measure of performance. We define *adaptive regret*, a notion that is a much better measure of how well our algorithm is adapting to the changing loss functions. We provide a procedure that converts any standard low-regret algorithm to one that provides low adaptive regret. We use an interesting mix of techniques, and use streaming ideas to make our algorithm efficient. This technique can be applied in many scenarios, such as portfolio management, online shortest paths, and the tree update problem, to name a few. Speaker: Seshadhri Comandur - Research Scientist - New Grad - Mountain View
Lecture - 1 Introduction to Data Structures and Algorithms Lecture Series on Data Structures and Algorithms by Dr. Naveen Garg, Department of Computer Science & Engineering ,IIT Delhi. For more details on NPTEL visit nptel.iitm.ac.in
Can you give us an update on rankings for long-tail searches? "Many are talking about losses of traffiic with long tail searches: I was wondering if you could give us an update on what is happening with Google right now? Caffeine update? Algorithm change? Temporary?" Brian, Seattle, WA
Algorithms Lesson 5: Linear and Binary Searching For this algorithms video lesson, we explain and demonstrate graphically how to perform the linear and binary search algorithms with a pseudocode implementations. Additionally, we give a speed comparison for the two searches. C++ code for the algorithms is available on our lesson page at Please submit all questions to our forum:
Free OLL Algorithms this is for people who use fridrich, and are currently learning full OLL or just want to know a few extra cases so, who is going to nationals?! i am!
Algorithms Lesson 4: Quicksort For this lesson, we explain and demonstrate graphically how to perform the quicksort algorithm with a pseudocode implementation. Please submit all questions to our forum:
USMLE ALGORITHMS: OBGYN-3rd trimester bleeding This video discusses Third Trimester Bleeding: Topic Covered: -Vasa Previa -Placenta Previa -Abrupto Placenta -Uterine Rupture This clip will help you distinguish the difference between 3rd Trimester Bleeding causes in a way where you will never get these questions wrong again.
Lecture -10 Greedy Algorithms -I Lecture Series on Design & ***ysis of Algorithms by Prof.Abhiram Ranade ,Prof.Sunder Vishwanathan, Department of Computer Science Engineering,IIT Bombay. For more details on NPTEL visit nptel.iitm.ac.in
Algorithms #1 - Bubblesort In this short video we take a look at the bubblesort sorting algorithm. It's one of the worst performing sorting algorithms, but it is also the easiest to explain. We also look at bubblesorts cousin shakersort.
How to solve a Rubik's Cube (Part One) -LIST OF ALGORITHMS- 1) Fi U Li Ui 2) Ri Di RD 3) UR Ui Ri Ui Fi UF 4) Ui Li ULUF Ui Fi 5) FRU Ri Ui Fi 6) RU Ri URUU Ri 7) UR Ui Li U Ri Ui L 8) Ri Di RD Music used in video: "Life Sentence" by The Dead Kennedys "Fu** The Facts" by John Zorn *Use of copyrighted material in this video meets "Fair Use" qualifications within United States Copyright Law*
Lecture - 2 Framework for Algorithms ***ysis Lecture Series on Design & ***ysis of Algorithms by Prof. Abhiram Ranade, Department of Computer Science Engineering,IIT Bombay. For more details on NPTEL visit nptel.iitm.ac.in
USMLE ALGORITHMS: MENINGITIS This algorithm is everything you need to know for the diagnosis and management of Meningitis for your exam. It is written and narrated by a USMLE Expert, and is to the point. All of Meningitis in less than 5 minutes. Look out for the book to be released late this Spring, "USMLE ALGORITHMS Step 3" .The textbook will comprise of Algorithms for the USMLE exams in the highest yield format supplemented by the highest yield clinical cases you need to know for the exam, as well as the highest yield CCS text written as of date. ENJOY the video algorithms as they are a prelude for what's to come!
Algorithms #3 - Selection Sort This time we take a look at how Selection Sort works, this being the third sorting algorithm in our series.
Running Large Graph Algorithms: Evaluation of Current State-Of-the-Art and Lessons Learned Google Tech Talk February 11, 2010 ABSTRACT Presented by Dr. Andy Yoo, Lawrence Livermore National Laboratory. Graphs have gained a lot of attention in recent years and have been a focal point in many emerging disciplines such as web mining, computational biology, social network ***ysis, and national security, just to name a few. These so-called scale-free graphs in the real world have very complex structure and their sizes already have reached unprecedented scale. Furthermore, most of the popular graph algorithms are computationally very expensive, making scalable graph ***ysis even more challenging. To scale these graph algorithms, which have different run-time characteristics and resource requirements than traditional scientific and engineering applications, we may have to adopt vastly different computing techniques than the current state-of-art. In this talk, I will discuss some of the findings from our studies on the performance and scalability of graph algorithms on various computing environments at LLNL, hoping to shed some light on the challenges in scaling large graph algorithms. Andy Yoo is a computer scientist in the Center for Applied Scientific Computing (CASC). His current research interests are scalable graph algorithms, high performance computing, large-scale data management, and performance evaluation. He has worked on the large graph problems since 2004. In 2005, he developed a scalable graph search algorithm and demonstrated it by searching a graph ...
Sorting Algorithms This video illustrates how several simple sorting algorithms operate, using people as the objects to be sorted. Produced by the Algorithmic Thinking class as part of Knight School 2009 at Menlo School. For people who know nothing about computer science but want to know what the heck is going on, here are brief descriptions of each sorting algorithm. Insertion Sort: Select each element in the list, and move it left until you hit somebody less than it. For example, when the element '2' is selected in the video, it moves left (shifting everybody right out of the way) until it encounters '1', when it is inserted back into the list. Selection Sort: Pass through the entire list, keeping track of the minimum element so far seen. When the pass is finished, select the global minimum and (in this simplified version of the algorithm) add it to a list of sorted elements. Repeat this, selecting the minimum element each time. Mergesort: Sorting a big list is too hard, so instead sort the first and last halves of the list, and then merge the sorted sublists. Of course, to sort each half-list we sort each quarter-list, and so forth. Eventually we get down to sorting a list with only two elements, which is easy! The merge can also be done very easily, by simply taking the smaller of the top elements of each sublist and repeating until the sublists are empty. In the video, the splitting of the original list into halves, quarters, etc. is not shown - for simplicity we start by immediately ...
USMLE ALGORITHMS: Bacterial Skin Infections USMLE Step 3 Bacterial Skin Infections Algorithm with Voice explanation from USMLE Expert. Topics: Impetigo Erysipelas Cellulitis Folliculitis Necrotizing Fasciitis