Distributed tree search (DTS) algorithm is a class of algorithms for searching values in an efficient and distributed manner. Their purpose is to iterate through a tree by working along multiple branches in parallel and merging the results of each branch into one common solution, in order to minimize time spent searching for a value in a tree-like data structure. The original paper was written in 1988 by Chris Ferguson and Richard E. Korf, from the University of California's Computer Science Department. They used multiple other chess AIs to develop this wider range algorithm. (Wikipedia).
Check if a binary tree is binary search tree or not
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have written a program in C/C++ to verify whether a given binary tree is binary search tree or not. For practice problems and more, visit: http://www.m
From playlist Data structures
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have discussed binary tree in detail. We have talked about different types of binary tree like "complete binary tree", "perfect binary tree" and "balance
From playlist Data structures
Discrete Math II - 11.4.1 Spanning Trees - Depth-First Search
We continue our study of trees by examining spanning trees. Spanning trees are subgraphs of a graph that contain all vertices of the original graph. The resulting subgraph is a tree, so the graph is connected and contains no cycles. In our first methodology, we will use a depth-first sear
From playlist Discrete Math II/Combinatorics (entire course)
Introduction to tree algorithms | Graph Theory
An introduction to tree algorithms. This video covers how trees are stored and represented on a computer. Support me by purchasing the full graph theory course on Udemy which includes additional problems, exercises and quizzes not available on YouTube: https://www.udemy.com/course/graph-t
From playlist Tree Algorithms
Related Videos: Binary search tree intro: https://youtu.be/JfSdGQdAzq8 Binary search tree insertions: https://youtu.be/LwpLXm3eb6A Binary search tree removals: https://youtu.be/8K7EO7s_iFE Binary search tree traversals: https://youtu.be/k7GkEbECZK0 Binary search tree code: https://youtu.be
From playlist Data structures playlist
Data structures: Binary Search Tree
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have discussed binary search tree data structure. Binary search is an efficient data structure in which we can store data to get search, insertion and de
From playlist Data structures
Get the Code Here: http://goo.gl/Zuatn Subscribe to Me: http://bit.ly/2FWQZTx Welcome to my tutorial on the Binary Tree in Java. On average a tree is more efficient then other data structures if you need to perform many different types of operations. In this tutorial I'll show you what a
From playlist Java Algorithms
Introduction to Spanning Trees
This video introduces spanning trees. mathispower4u.com
From playlist Graph Theory (Discrete Math)
The video explains MuZero! MuZero makes AlphaZero more general by constructing representation and dynamics models such that it can play games without a perfect model of the environment. This dynamics function is unique because of the way it's hidden state is tied into the policy and value
From playlist Game Playing AI: From AlphaGo to MuZero
This video explains AlphaGo Zero! AlphaGo Zero uses less prior information about Go than AlphaGo. Whereas AlphaGo is initialized by supervised learning on human experts mappings from state to action; AlphaGo Zero is trained from scratch through self-play. AlphaGo Zero achieves this by comb
From playlist Game Playing AI: From AlphaGo to MuZero
The Evolution of AlphaGo to MuZero
This video covers the developments progression from AlphaGo to AlphaGo Zero to AlphaZero, and the latest algorithm, MuZero. These algorithms from the DeepMind team have gone from superhuman Go performance up to 57 different Atari games. Hopefully this video helps explain how these are rela
From playlist Game Playing AI: From AlphaGo to MuZero
Lecture 19: Data Structures and Algorithms - Richard Buckland
we start looking at the problem of searching. Lecture 19 of COMP1927 "Data Structures and Algorithms" by Richard Buckland UNSW, 2009
From playlist CS2: Data Structures and Algorithms - Richard Buckland
Kyle Cranmer: "Quarks, hierarchical clustering, and combinatorial optimization"
Deep Learning and Combinatorial Optimization 2021 "Quarks, hierarchical clustering, and combinatorial optimization" Kyle Cranmer - New York University Abstract: Combinatorial optimization isn’t a topic that is discussed much in experimental particle physics, but it is hiding in one of th
From playlist Deep Learning and Combinatorial Optimization 2021
This video explains the details behind AlphaGo! AlphaGo uses policy and value networks to reduce the search space in MCTS! Thanks for watching! Please Subscribe! Paper Link: https://www.nature.com/articles/nature16961
From playlist Game Playing AI: From AlphaGo to MuZero
This video explains AlphaZero! AlphaZero makes slight modifications to AlphaGo Zero and generalizes the game from Go to Chess and Shogi as well. AlphaZero outplays Chess algorithms that uses a more exhaustive Alpha-Beta search engine compared to MCTS and uses handcrafted features from expe
From playlist Game Playing AI: From AlphaGo to MuZero
Arcane Algorithm Archive: Tree Traversal -- Day 1-ish
Hey guys, I screwed up big time, but we got somewhere at least. Working on tree traversal visualizations! -- Watch live at https://www.twitch.tv/simuleios
From playlist Algorithm-archive
Vinod Nair: "Solving Mixed Integer Programs Using Neural Networks"
Deep Learning and Combinatorial Optimization 2021 "Solving Mixed Integer Programs Using Neural Networks" Vinod Nair - DeepMind Technologies Abstract: Mixed integer programming (MIP) solvers employ many heuristics to solve large-scale instances that are encountered in practice. However, t
From playlist Deep Learning and Combinatorial Optimization 2021
Using Semantic Search to Find GIFs
Vector search powers some of the most popular services in the world. It serves your Google results, delivers the best podcasts on Spotify, and accounts for at least 35% of consumer purchases on Amazon. In this article, we will use vector search applied to language, called semantic search,
From playlist Quick Projects
Stanford Seminar - The Case for Learned Index Structures
EE380: Computer Systems Colloquium Seminar The Case for Learned Index Structures Speaker: Alex Beutel and Ed Chi, Google Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a pos
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series