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

3 views • 87 slides

Memory-unsafe languages like C and C++ are prone to Use-After-Free (UAF) vulnerabilities. PUMM introduces execution unit partitioning to efficiently tackle this issue. By segregating and managing execution units, PUMM aims to prevent UAF exploits and enhance software security.

0 views • 31 slides

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

3 views • 19 slides

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

2 views • 48 slides

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

0 views • 20 slides

An open-source tool called TritonPart offers a constraints-driven approach for general partitioning in VLSI physical design. It replaces hMETIS and is integrated with OpenROAD, providing features like multi-way partitioning and embedding-aware techniques. TritonPart shows significant improvements ov

1 views • 20 slides

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

1 views • 75 slides

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

3 views • 37 slides

The stable maintenance of low-copy-number plasmids in bacteria relies on partition mechanisms that ensure proper positioning during cell division. Different from high-copy-number plasmids, which rely on random diffusion, low-copy-number plasmids require regulated partitioning mechanisms to prevent d

0 views • 14 slides

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.

0 views • 84 slides

Graph Theory Matchings have a rich history dating back to the 9th century AD. Distinct Representatives and Hall's Theorem play important roles in determining matchings in graphs. Understanding concepts like bipartite graphs, maximum matchings, and Hall's Marriage Theorem is essential in graph theory

1 views • 12 slides

In Year 2 Mathematics Week 1, students will be practicing addition of two-digit numbers using methods like partitioning into tens and ones and the expanded column method. Parents are encouraged to help and show different methods to their children, such as drawing dienes or using squared paper for la

1 views • 10 slides

Freebase was initially created in 2005 as an open shared database of knowledge, later acquired by Google and absorbed into the Google Knowledge Graph. Its approach included crowdsourcing updates and additions, focusing on data rather than text. The schema of Freebase included around 1500 types, 3500

1 views • 12 slides

In this lecture, Kasey Champion covers a wide range of topics including graph algorithms, data structures, coding projects, and important midterm topics for CSE 373. The lecture emphasizes understanding ADTs, data structures, asymptotic analysis, sorting algorithms, memory management, P vs. NP, heap

0 views • 38 slides

Equivalence class testing is a software testing technique that involves dividing input values into classes for effective testing coverage. Equivalence classes are defined mathematically as subsets of a given set, ensuring partitioning and mutual exclusivity. By applying equivalence partitioning, tes

1 views • 21 slides

Uncover the power of Microsoft Graph through accessing files, extending Microsoft 365 experiences, and utilizing the gateway to Microsoft Cloud data. Learn about authentication options and how to interact with the Microsoft Graph Direct REST API.

1 views • 37 slides

Learn how Azure Cosmos DB leverages partitioning to automatically scale data globally. Discover the importance and types of partitioning, logical and physical partitions, best practices, and more.

0 views • 24 slides

Operating systems employ various memory management techniques such as fixed partitioning, dynamic partitioning, paging, segmentation, and virtual memory to efficiently utilize memory resources. These techniques help in organizing memory allocation for programs, managing fragmentation, and optimizing

0 views • 17 slides

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

0 views • 13 slides

Freebase was launched in 2005 as an open database of knowledge, initially populated with Wikipedia data and later incorporating crowdsourced updates. Acquired by Google in 2010, it was transitioned into Google's Knowledge Graph before being decommissioned in 2016. The schema contained around 1500 ty

4 views • 12 slides

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.

0 views • 17 slides

Learn how to identify different graph shapes such as symmetric, skewed, and uniform, and understand descriptors like unimodal and bimodal. Explore practical examples and visual aids to enhance your graph interpretation skills.

0 views • 19 slides

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

2 views • 18 slides

Investigating natural language interfaces for querying structured MOF data stored in a knowledge graph, this project focuses on developing strategies using NLP to translate NL questions to KG queries. The MOF-KG integrates datasets, enabling query, computation, and reasoning for deriving new knowled

0 views • 13 slides

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

1 views • 19 slides

The content discusses the concepts of graph connectivity and single element recovery using linear and OR queries. It delves into the strategies, algorithms, and tradeoffs involved in determining unknown vectors, edges incident to vertices, and spanning forests in graphs. The talk contrasts determini

0 views • 28 slides

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

0 views • 55 slides

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

0 views • 14 slides

This class introduces the fundamentals of distributed graph algorithms focusing on network modeling, complexity measures, solving graph problems, and comparing distributed vs. centralized algorithms. It covers topics such as the LOCAL model, synchronous rounds, communication rounds, computation time

0 views • 17 slides

Delve into the fascinating world of graph colorings, chromatic polynomials, and notable conjectures in discrete geometry. Explore the impact of June Huh in bringing Hodge theory to combinatorics and his proof of various mathematical conjectures. Uncover the significance of the four-color theorem, co

0 views • 17 slides

In this presentation, the speaker discusses the use of triangle partitioning and linear optimization techniques to analyze hockey team lines. The goal is to find chemistry between players, allocate ice time effectively, and match up against opposing lines for a better chance of winning games. Tradit

0 views • 16 slides

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

0 views • 15 slides

This research delves into multimodal semantic indexing methods for image retrieval, focusing on extending Latent Semantic Indexing (LSI) and probabilistic LSI to a multi-modal setting. Contributions include the refinement of graph models and partitioning algorithms to enhance image retrieval from tr

0 views • 28 slides

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

0 views • 17 slides

Explore the QuickSort algorithm with details on the worst-case time complexity, partitioning process, recursive method, and example scenarios. Understand how QuickSort efficiently sorts arrays by choosing a pivot, comparing elements, and recursively partitioning the array until sorted. Dive into the

0 views • 19 slides

This content delves into various aspects of scaling services, including partitioning, hashing, and key-value storage. It discusses vertical and horizontal scalability, the chaotic nature of horizontal scaling, techniques for partitioning data, and case studies like Amazon Dynamo. The importance of p

0 views • 48 slides

Delve into the intricacies of multiplication through hands-on activities using arrays, partitioning, and understanding the commutative property. Discover how arrays can help visualize multiplication, learn to partition numbers for easier calculations, and grasp the concept of multiplying by powers o

0 views • 17 slides

Get your whiteboards ready for a fun math activity on number partitioning! Practice partitioning numbers into ones and tens, then solve equations by adding the ones and tens separately. Check out the examples provided to understand the concept better.

0 views • 58 slides

BiGraph is a distributed graph partitioning algorithm designed for bipartite graphs, offering a scalable solution for big data processing in Machine Learning and Data Mining applications. The algorithm addresses the limitations of existing partitioning methods by efficiently distributing and managin

0 views • 45 slides

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

0 views • 41 slides