The efficient coding hypothesis was proposed by Horace Barlow in 1961 as a theoretical model of sensory coding in the brain. Within the brain, neurons communicate with one another by sending electrical impulses referred to as action potentials or spikes. One goal of sensory neuroscience is to decipher the meaning of these spikes in order to understand how the brain represents and processes information about the outside world. Barlow hypothesized that the spikes in the sensory system formed a neural code for efficiently representing sensory information. By efficient Barlow meant that the code minimized the number of spikes needed to transmit a given signal. This is somewhat analogous to transmitting information across the internet, where different file formats can be used to transmit a given image. Different file formats require different number of bits for representing the same image at given distortion level, and some are better suited for representing certain classes of images than others. According to this model, the brain is thought to use a code which is suited for representing visual and audio information representative of an organism's natural environment . (Wikipedia).
(IC 4.12) Optimality of Huffman codes (part 7) - existence
We prove that Huffman codes are optimal. In part 7, we show that there exists an optimal code for any given p. A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F
From playlist Information theory and Coding
Introduction to Algorithms - What are they and how are they useful?
#3B1B #SoMe2 This is my submission for this year's SoME, SoME2!! I hope you enjoy, and please feel free to leave any comments. Any feedback is hugely appreciated~! ーーーーーーーーーーーーーーーーーーーーーーー Time Stamps: 00:00 Intro 00:37 Introduction to Algorithms 03:47 Exploring Algorithms - Binary Searc
From playlist Summer of Math Exposition 2 videos
(IC 4.5) An issue with Huffman coding
Huffman coding does not work well when the source has low entropy, since codewords must have integer-valued lengths. A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F
From playlist Information theory and Coding
(IC 3.5) Bounds on optimal expected length
Using Shannon coding, one can get within 1 of the entropy. This gives an upper bound on the expected codeword length of an optimal code. A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F
From playlist Information theory and Coding
Searching and Sorting Algorithms (part 4 of 4)
Introductory coverage of basic searching and sorting algorithms, as well as a rudimentary overview of Big-O algorithm analysis. Part of a larger series teaching programming at http://codeschool.org
From playlist Searching and Sorting Algorithms
Random Oracle - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
(IC 5.8) Near optimality of arithmetic coding
The expected encoded length of the entire message is within 2 bits of the ideal encoded length (the entropy), assuming infinite precision. A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F
From playlist Information theory and Coding
Feynman Bytes Ep 3: Only a Guess (Code)
How do we adapt humanity’s best problem-solving technique, science, to writing code? Professor Richard Feynman was a Nobel-prize winning physicist & a genius. He was also a great educator and thinker on the topic of science. This occasional series on the Continuous Delivery channel looks
From playlist Feynman Bytes
Mathematica and Computational Thinking Applied to Engineering
Exergetika is a start-up company, whose value proposal is the application of computational thinking to solve engineering problems that from its conception has been inspired in the computational possibilities offered by Wolfram Mathematica and Wolfram System Modeler. In this conference Exer
From playlist Wolfram Technology Conference 2020
(IC 3.9) Source coding theorem (optimal lossless compression)
Proof of Shannon's "Source coding theorem", characterizing the entropy as the best possible lossless compression (using block codes) for a discrete memoryless source. A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F
From playlist Information theory and Coding
MIT 6.006 Introduction to Algorithms, Spring 2020 Instructor: Jason Ku View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY The goal of this introductions to algorithms class is to teach you to so
From playlist MIT 6.006 Introduction to Algorithms, Spring 2020
A History of Primes - Manindra Agrawal [2002]
2002 Annual Meeting Clay Math Institute Manindra Agrawal, American Academy of Arts and Sciences, October 2002
From playlist Number Theory
Non-Black-Box Derandomization - Roei Tell
Computer Science/Discrete Mathematics Seminar II Topic: Non-Black-Box Derandomization Speaker: Roei Tell Affiliation: Member, School of Mathematics Date: March 01, 2022 This is the third and final talk in the joint series with Lijie Chen. The talk will NOT rely on the technical contents
From playlist Mathematics
RubyConf 2021 - The Mindset of Debugging by Kyle d'Oliveira
We, as developers, spend a large portion of our time debugging software. Sometimes the problems are easy to understand, but many times they are not and we are thrown into unfamiliar code and are expected to quickly find the problem and craft a solution. However, honing the skill of debuggi
From playlist RubyConf 2021
Perfect Cipher - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Testing Sparsity over Known and Unknown Bases by Arnab Bhattacharyya
Statistical Physics Methods in Machine Learning DATE:26 December 2017 to 30 December 2017 VENUE:Ramanujan Lecture Hall, ICTS, Bengaluru The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the "th
From playlist Statistical Physics Methods in Machine Learning
Derandomization and its connections throughout complexity theory - Roei Tell
Computer Science/Discrete Mathematics Seminar II Topic: Derandomization and its connections throughout complexity theory Speaker: Roei Tell Affiliation: Member, School of Mathematics Date: February 15, 2022 This is the first talk in a three-part series presented together with Lijie Ch
From playlist Mathematics
AI Weekly Update - December 28th, 2020 (#26)!
Thank you for watching! Please Subscribe! Content Links: Data-Efficient Image Transformers: https://ai.facebook.com/blog/data-efficient-image-transformers-a-promising-new-technique-for-image-classification/ Pre-Training a Language Model without Human Language: https://arxiv.org/pdf/2012.1
From playlist AI Research Weekly Updates
Random Oracle Solution - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Nexus Trimester - Sidharth Jaggi (CUHK)
Reliable Deniable Communication : hiding messages in Noise Sidharth Jaggi (CUHK) March 01, 2016 Abstract: The urge to communicate, to speak and be heard, is a fundamental human need. However, embedded within our increasingly sophisticated communication networks, Big Brother is often watch
From playlist Nexus Trimester - 2016 - Central Workshop