Armavita is a Houston SEO company that provides a full range of digital marketing services including SEO consultancy services to small and large businesses across the globe. With our years of experience and a number of strategies we help you improve your rankings and encourage organic site traffic and revenue.
Spatial co-location pattern mining refers to the task of discovering the group of objects or events that co-occur at many places. Extracting these patterns from spatial data is very difficult due to the complexity of spatial data types, spatial relationships, and spatial auto-correlation. We model the co-location pattern discovery as a clique enumeration problem over a neighborhood graph (which is materialized using a distributed graph database). Further, we propose three new traversal based algorithms, namely CliqueEnumG, CliqueEnumK and CliqueExtend. These algorithms allow for a trade-off between time and memory requirements and support interactive data analysis without having to recompute all the intermediate results.
Trademark registration from Legal Legends helps establish ownership and protect brand of an entity. A trademark is a visual symbol, which may be a word, name, device, label or numerals used by a business to distinguish it goods or services from other similar goods or services originating from a different business. Register your brand and Logo in South Africa with the Online trademark registration service from Legal Legends.
Dedicated Developers is a top-tier Web and Mobile Application Development company. The company was founded in 2007 and employs over 100 employees globally. Their industry leadership stems from their unique model that combines US-based project management and leadership with access to top talent in The UK, Philippines, and Argentina.
Hi there -- one of the authors of the paper here. Optimal stopping problems constitute an important class of stochastic control problems, with many real applications, such as pricing financial options. Typically they are solved using approximate dynamic programming methods, which involve coming up with some approximation of the value function or the continuation value function.
In this paper, we take a different approach, where we represent the stopping policy as a tree, and propose a methodology for learning this tree from the data; so in the same way that one comes up with a tree for predicting a binary label in classification, or predicting a continuous value in regression, one obtains a tree that prescribes an action for each possible state. We show using a standard benchmark problem in option pricing that these tree policies perform very well, while being as simple and interpretable as tree models used in other areas of machine learning. We appreciate any questions or comments!
Ready to Design a Brand New Fantasy Sports Website for You!
Mobiweb Technologies have expertise and years of experience in developing fantasy sports software for games, platforms, and websites for all type of sports such as football, cricket, basketball, baseball, golf, hockey, soccer and auto racing. We are the leading providers of Fantasy Sports software, website and mobile application development. We have developed interactive and feature rich Fantasy Sports solutions for a number of businesses which are running successfully by having millions of users.
Are you looking for Online Trademark Registration for your business? Register your brand and Logo in South Africa with the trademark registration service from Legal Legends. Trademark Registry gives the protection to the brand name with the logo in their respective trademark class. Legal Legends is the leading online legal service provider company in SA. To get any type of legal services from us, just visit our official website now.
We were at ECCV 2 weeks ago. This is a recap on two verticals (we voluntarily did not made the recap exhaustive)
- new nn architectures (mostly for detection and segmentation purposes)
- 6D pose estimation using RGB (not RGB-D) images and the 3D model.
Hope you find this interesting.
OP here. This is something I've been pondering recently and have seen to some extent in all companies that I have worked with. I've found that objective discussions, based on mutually agreed pros & cons, are often more important than the specific machine-learning model used.