4 step sketch
A 4-step sketching process to generate and refine ideas through note-taking, idea generation, rapid sketching, and solution sketching.
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Graph Machine Learning Overview: Traditional ML to Graph Neural Networks
Explore the evolution of Machine Learning in Graphs, from traditional ML tasks to advanced Graph Neural Networks (GNNs). Discover key concepts like feature engineering, tools like PyG, and types of ML tasks in graphs. Uncover insights into node-level, graph-level, and community-level predictions, an
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Localised Adaptive Spatial-Temporal Graph Neural Network
This paper introduces the Localised Adaptive Spatial-Temporal Graph Neural Network model, focusing on the importance of spatial-temporal data modeling in graph structures. The challenges of balancing spatial and temporal dependencies for accurate inference are addressed, along with the use of distri
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Graph Neural Networks
Graph Neural Networks (GNNs) are a versatile form of neural networks that encompass various network architectures like NNs, CNNs, and RNNs, as well as unsupervised learning models such as RBM and DBNs. They find applications in diverse fields such as object detection, machine translation, and drug d
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Understanding Neo4j Graph Database Fundamentals
This comprehensive presentation delves into the fundamentals of Neo4j graph database, covering topics such as the definition of graph databases, reasons for their usage, insights into Neo4j and Cypher, practical applications like data flow analysis, and hands-on instructions on creating and querying
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Understanding Breadth-First Search (BFS) Algorithm for Graph Searching
This content delves into the Breadth-First Search (BFS) algorithm, a fundamental graph searching technique. It explains the step-by-step process of BFS, from initializing the graph to traversing vertices in a specific order. Through detailed visual representations, you will gain insights into how BF
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Exploring Graph-Based Data Science: Opportunities, Challenges, and Techniques
Graph-based data science offers a powerful approach to analyzing data by leveraging graph structures. This involves using graph representation, analysis algorithms, ML/AI techniques, kernels, embeddings, and neural networks. Real-world examples show the utility of data graphs in various domains like
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Understanding Graph Theory: Friendship Theorem and Freshman's Dream
Explore the intriguing concepts of the Friendship Theorem and Freshman's Dream in graph theory along with examples and visual illustrations. Learn about common friends, relationships between vertices and edges, and what defines a graph in a concise yet comprehensive manner.
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Foster Creativity Through Brainstorming and Sketching Activities
Embrace brainstorming techniques like free-for-all and forced association to generate innovative ideas. Follow rules of no criticism and encourage quantity over quality. Utilize sketching to visually communicate concepts effectively. Engage in fun activities like building the Tower of Benton to appl
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Exploring Deep Graph Theory: Philosophical Implications and Misconceptions
Delve into the realm of Deep Graph Theory where graph theory statements are analyzed beyond their conventional scope to uncover philosophical insights and correct misunderstandings. Discover the essence of trees, forests, and the unique relationship where every tree is regarded as a forest. Addition
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Understanding Graph Theory Fundamentals
Delve into the basics of graph theory with topics like graph embeddings, graph plotting, Kuratowski's theorem, planar graphs, Euler characteristic, trees, and more. Explore the principles behind graphs, their properties, and key theorems that define their structure and connectivity.
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Association Rules with Graph Patterns: Exploring Relationships in Data
Dive into the world of association rules with graph patterns, where relationships and connections are analyzed through nodes and edges. Discover how to define association rules, identify customers, and uncover interesting patterns using graph-based techniques. Explore traditional and graph-pattern a
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Solving the Professors to Coffee Lounge Problem: A Graph Theory Approach
An intriguing mathematical problem is presented where new faculty members at TIMS must be assigned to coffee lounge alcoves in a way that ensures no two new members meet after the first day. By constructing a graph based on meet-up timings, analyzing clashes, and determining intervals, this scenario
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Exploring the Impact of Randomness on Planted 3-Coloring Models
In this study by Uriel Feige and Roee David from the Weizmann Institute, the effect of randomness on planted 3-coloring models is investigated. The research delves into the NP-hard nature of 3-coloring problems, introducing a hosted coloring framework that involves choices like the host graph and th
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Managing Large Graphs on Multi-Cores with Graph Awareness
This research discusses the challenges in managing large graphs on multi-core systems and introduces Grace, an in-memory graph management and processing system with optimizations for graph-specific and multi-core-specific operations. The system keeps the entire graph in memory in smaller parts and p
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Sketching Techniques for Efficient Numerical Linear Algebra on Massive Data Sets
Explore how sketching methods can be applied in numerical linear algebra to handle massive data sets efficiently. David Woodruff of IBM Almaden discusses using randomized approximations for algorithms aiming for nearly linear time complexity. Applications include analyzing internet traffic logs, fin
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Sketching as a Tool for Algorithmic Design by Alex Andoni - Overview
Utilizing sketching in algorithmic design, Alex Andoni from Columbia University explores methodologies such as succinct efficient algorithms, dimension reduction, sampling, metric embeddings, and more. The approach involves numerical linear algebra, similarity search, and geometric min-cost matching
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Understanding Sketching and Constraints in SolidWorks
Explore the process of sketching in SolidWorks, from defining dimensions and geometric constraints to understanding sketch states. Learn how to manage underdefined, fully defined, and overdefined sketches, along with tips for adding, editing, and deleting constraints effectively.
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Maria's Bike Journey Graph Analysis
Maria's bike journey graph depicts her distance from home as she rode to meet friends and run errands before returning home. The graph shows her stops for errands, changes in direction, and her path back home. By interpreting the key features of the graph, such as intercepts and intervals, we can an
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Balanced Graph Edge Partition and Its Practical Applications
Balanced graph edge partitioning is a crucial problem in graph computation, machine learning, and graph databases. It involves partitioning a graph's vertices or edges into balanced components while minimizing cut costs. This process is essential for various real-world applications such as iterative
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Understanding Spanning Trees and Minimum Spanning Trees
Explore the concept of spanning trees and minimum spanning trees in graph theory through an in-depth lecture outline covering topics like Cut Property, Cycle Property, Kruskal's Algorithm, and more. Delve into the significance of Minimum Spanning Trees (MSTs) as the lowest-cost spanning tree of a gr
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Graph Pattern Matching Challenges and Solutions
Graph pattern matching in social networks presents challenges such as costly queries, excessive results, and query focus issues. The complexity of top-k and diversified pattern matching problems requires heuristic algorithms for efficient solutions. Finding best candidates for project roles involves
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LD-Sketch: Distributed Sketching Design for Anomaly Detection in Network Data Streams
LD-Sketch is a novel distributed sketching design for accurate and scalable anomaly detection in network data streams, addressing challenges such as tracking heavy keys in real-time across a vast key space. By combining high accuracy, speed, and low space complexity, LD-Sketch enables efficient heav
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Understanding Small Set Expansion in Johnson Graphs
In this detailed piece, Subhash Khot, Dor Minzer, Dana Moshkovitz, and Muli Safra explore the fascinating concept of Small Set Expansion in Johnson Graphs. The Johnson Graph is defined as a representation where nodes are sets of size K in a universe of size N, and two sets are connected if they inte
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Vertex-Centric Programming for Graph Neural Networks
Seastar presents a vertex-centric programming approach for Graph Neural Networks, showcasing better performance in graph analytic tasks compared to traditional methods. The research introduces the SEAStar computation pattern and discusses GNN programming abstractions, execution, and limitations. Dee
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Graph Property Testing and Algorithms Overview
Explore testable bounded degree graph properties, sparse graphs, d-bounded degree graphs, hyperfinite graphs, arboricity, maximum matching algorithms, and sublinear time approximation algorithms in graph data streams. Learn about various graph models and properties with examples, showcasing the impo
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Understanding Graph Modeling and DFS Applications
Explore the world of graph modeling and DFS applications through lectures on graph vocabulary, edge classification in directed graphs, and the use of DFS to find cycles. Discover the significance of tree edges, back edges, forward edges, and cross edges in graph traversal. Learn how DFS can be utili
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Graph-Based Knowledge Representation in Modelling: A Comprehensive Overview
This content delves into graph-based knowledge representation in modelling, detailing concepts such as recipe-ingredient relationships, formalisms for generalizing graph representation, and conceptual graphs by John F. Sowa. It explores how different interpretations describe the association between
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Understanding Graph Databases and Neo4j
Graph databases offer a flexible way to manage data by representing relationships between nodes. Neo4j is a popular graph database system that uses Cypher for querying. This guide provides insights into graph database concepts, advantages, and getting started with Neo4j, including creating nodes and
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Solving Train Track Problems Using Interval Graphs and Graph Coloring
Presented by Manvitha Nellore, this content addresses real-world train track problems in busy cities by proposing solutions through interval graphs and graph theory. The approach involves allotting tracks to trains by scheduling with time intervals to avoid conflicts. An interval graph is defined, a
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Mastering Sketching Techniques: Oblique, Isometric, and Shading Tips
Learn how to create 3D effects in your sketches using oblique and isometric sketching methods, along with shading techniques to add depth and dimension. Master the art of drawing cubes and other shapes with step-by-step instructions and visual examples. Enhance your sketching skills with tips on hat
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Sketching Graphs of Functions: Techniques and Examples
The art of sketching graphs of functions involves representing specific shapes and behaviors through labeled diagrams. This lesson highlights key details to keep in mind when sketching functions, such as labeling axes, maximum and minimum values, intercepts, symmetry, and asymptotes. Two examples of
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Sketching and Embedding Equivalence for Norms in Metric Spaces
Sketching and embedding techniques are explored by Alexandr Andoni, Robert Krauthgamer, and Ilya Razenshteyn in the context of metric spaces. This research delves into the equivalence between sketching and embedding for various norms, addressing topics such as compressing high-dimensional objects, s
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The Sketching Approach to Program Synthesis
The Sketching Approach to Program Synthesis, presented by Armando Solar-Lezama, introduces a new programming model focused on localized synthesis, allowing programmers to control implementation strategy. Sketches, programs with holes, enable constraining the set of solutions considered by the synthe
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Enhancing Efficiency in Sketch-based Monitoring for Programmable Switches
SketchLib introduces advancements in sketching algorithms to enable efficient monitoring on programmable switches. The tool bridges gaps between existing sketches for CPUs and programmable switches, offering resource optimizations and API calls to enhance performance and reduce resource consumption
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Understanding Sketching and Locality Sensitive Hashing in Data Mining
Explore the concepts of Jaccard Similarity and Cosine Similarity in data mining, along with their applications in recommendation systems and finding near-duplicates. Discover how Sketching and Locality Sensitive Hashing techniques help in efficiently identifying similar items and solving the Nearest
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Data Processing and Analysis for Graph-Based Algorithms
This content delves into the preprocessing, computing, post-processing, and analysis of raw XML data for graph-based algorithms. It covers topics such as data ETL, graph analytics, PageRank computation, and identifying top users. Various tools and frameworks like GraphX, Spark, Giraph, and GraphLab
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Understanding Graph Algorithms for Connectivity and Shortest Paths
Graph algorithms play a crucial role in solving problems represented as networks, maps, paths, plans, and resource flow. This content delves into ways to find connectivity in graphs and algorithms for determining shortest paths. It discusses graph representations using adjacency matrices and lists,
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Insights into Cliques and Independent Sets in Graph Theory
Exploring the concepts of cliques, independent sets, and theorems in graph theory regarding enemy relationships, maximum number of edges in 3-free graphs, and properties of multipartite graphs. The propositions and theorems discussed shed light on graph structures and their properties, providing val
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Sketching Activities and Fun Facts about Iron Man
Join the captivating sketching activity and learn interesting facts about the worldwide famous Marvel character, Iron Man. Delve into the creative world of sketching while exploring the remarkable achievements of Iron Man in July 2009, including its substantial worldwide grossing.
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