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How Supply Chain Lost Its Mojo
"Bad Conferences on Steroids. With the pink ghetto marketing organization focused on leads and placement of speakers, there is a strong investment in “conference sponsorships.” In England, we have a plethora of event organizers that roll out many questionable events largely funded by technology companies. Business users attend free, but the primary goal is to provide a forum for technologists to advertise their products (I feel this way about EFT, IE Group, SCOPE, World Trade Group). The reason? There is no vetting of presenters."
market-driven  value  chains  networks  new  technologies  mojo  pink  ghetto  marketing  supply  chain  management  proposition 
yesterday by jonerp
How social media took us from Tahrir Square to Donald Trump - MIT Technology Review
To understand how digital technologies went from instruments for spreading democracy to weapons for attacking it, you have to look beyond the technologies themselves.
social-media  social-engineering  networks  public-policy  politics  political-economy 
yesterday by Vaguery
Internet as a city
If the Internet were a city, what would be its roads, buildings, and parks? How do people, businesses and governing bodies produce insights into the qualitative characteristics of distribution beyond the tired triptych of centralized, decentralized, and distributed?

In this hands-on workshop, wel examine decentralized forms of networking through the lenses of cities, urbanism, and architecture. In small groups, participants are provided with “urban” elements to construct landscapes that tease out models of decentralization and governance for the “Internet as a city.” Warm up exercises help attendants image websites as a building, and mapping trails as browsing experiences.

We extend this exploration to modes of governance in decision making, and notions of “public space” or the commons.
networks  smart_cities  urban_form  infrastructure  games 
yesterday by shannon_mattern
Discovery Europe GIF - Find & Share on GIPHY
GIF cars, spinning, speed, discovery, silver, engine, discovery channel, showcase, convertible, platinum, alfa romeo, dream car, 360 spin, discovery networks, petrolheads, wheeler dealers, car showcase, hood up, spider quadrifoglio Giphy https://ift.tt/2P6zOCH ______ http://goo.gl/3oHDPV
cars  spinning  speed  discovery  silver  engine  channel  showcase  convertible  platinum  alfa  romeo  dream  car  360  spin  networks  petrolheads  wheeler  dealers  ho 
2 days ago by architektura
Discovery Europe GIF - Find & Share on GIPHY
GIF red, cars, spinning, speed, discovery, engine, discovery channel, showcase, porche, dream car, 360 spin, discovery networks, petrolheads, car showcase, wheeler dealers Giphy https://ift.tt/2P6znZ5 ______ http://goo.gl/3oHDPV
red  cars  spinning  speed  discovery  engine  channel  showcase  porche  dream  car  360  spin  networks  petrolheads  wheeler  dealers  wynajem  samochody  auta 
2 days ago by architektura
giphy.com
GIF red, cars, spinning, speed, discovery, engine, discovery channel, showcase, porche, dream car, 360 spin, discovery networks, petrolheads, car showcase, wheeler dealers Giphy https://ift.tt/2B9UtCR ______ http://goo.gl/3oHDPV
red  cars  spinning  speed  discovery  engine  channel  showcase  porche  dream  car  360  spin  networks  petrolheads  wheeler  dealers  wynajem  samochody  auta 
2 days ago by architektura
Discovery Europe GIF - Find & Share on GIPHY
GIF cars, spinning, discovery, engine, discovery channel, jeep, showcase, doors open, 360 spin, discovery networks, petrolheads, car showcase, wheeler dealers, jeep grand wagoneer Giphy https://ift.tt/2KREn0q ______ http://goo.gl/3oHDPV
cars  spinning  discovery  engine  channel  jeep  showcase  doors  open  360  spin  networks  petrolheads  car  wheeler  dealers  grand  wagoneer  wynajem  samochody  auta 
2 days ago by architektura
[1705.02801] Graph Embedding Techniques, Applications, and Performance: A Survey
Graphs, such as social networks, word co-occurrence networks, and communication networks, occur naturally in various real-world applications. Analyzing them yields insight into the structure of society, language, and different patterns of communication. Many approaches have been proposed to perform the analysis. Recently, methods which use the representation of graph nodes in vector space have gained traction from the research community. In this survey, we provide a comprehensive and structured analysis of various graph embedding techniques proposed in the literature. We first introduce the embedding task and its challenges such as scalability, choice of dimensionality, and features to be preserved, and their possible solutions. We then present three categories of approaches based on factorization methods, random walks, and deep learning, with examples of representative algorithms in each category and analysis of their performance on various tasks. We evaluate these state-of-the-art methods on a few common datasets and compare their performance against one another. Our analysis concludes by suggesting some potential applications and future directions. We finally present the open-source Python library we developed, named GEM (Graph Embedding Methods, available at this https URL), which provides all presented algorithms within a unified interface to foster and facilitate research on the topic.

--Ok as a survey. Works from the following definition of graph embedding.

(Graph embedding) Given a graph G=(V,E),a graph embedding is a mapping f:vi→yi∈Rd∀∈[n]such that d |V |and the function f preserves some proximity measure defined on graph G
graph_theory  survey  geometry  topological_data_analysis  networks  ? 
2 days ago by rvenkat
Representation Learning on Networks
Researchers in network science have traditionally relied on user-defined heuristics to extract features from complex networks (e.g., degree statistics or kernel functions). via Pocket
graphs  learn  machine  networks 
5 days ago by kintopp
node2vec
Learning useful representations from highly structured objects such as graphs is useful for a variety of machine learning applications. Besides reducing the engineering effort, these representations can lead to greater predictive power. via Pocket
graphs  machine  networks  tools 
5 days ago by kintopp

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