The development of algorithms for unsupervised pattern recognition by nonlinear clustering is a notable problem in data science. Markov clustering (MCL) is a renowned algorithm that simulates stochastic flows on a network of sample similarities to detect the structural organization of clusters in the data, but it has never been generalized to deal with data nonlinearity. Minimum Curvilinearity (MC) is a principle that approximates nonlinear sample distances in the high-dimensional feature space by curvilinear distances, which are computed as transversal paths over their minimum spanning tree, and then stored in a kernel. Here we propose MC-MCL, which is the first nonlinear kernel extension of MCL and exploits Minimum Curvilinearity to enhance the performance of MCL in real and synthetic data with underlying nonlinear patterns. MC-MCL is compared with baseline clustering methods, including DBSCAN, K-means and affinity propagation. We find that Minimum Curvilinearity provides a valuable framework to estimate nonlinear distances also when its kernel is applied in combination with MCL. Indeed, MC-MCL overcomes classical MCL and even baseline clustering algorithms in different nonlinear datasets.

We propose a projection pursuit (PP) algorithm based on Gaussian mixture models (GMMs). The negentropy obtained from a multivariate density estimated by GMMs is adopted as the PP index to be maximised. For a fixed dimension of the projection subspace, the GMM-based density estimation is projected onto that subspace, where an approximation of the negentropy for Gaussian mixtures is computed. Then, Genetic Algorithms (GAs) are used to find the optimal, orthogonal projection basis by maximising the former approximation. We show that this semi-parametric approach to PP is flexible and allows highly informative structures to be detected, by projecting multivariate datasets onto a subspace, where the data can be feasibly visualised. The performance of the proposed approach is shown on both artificial and real datasets.

WASHINGTON – All but the smallest civilian drones would have to broadcast radio tracking data to ensure greater safety and prevent terrorism under a sweeping proposal unveiled by U.S. regulators Thursday. The long-awaited draft rules call for a massive new tracking network for everything from toys to larger commercial drones so that law enforcement can spot the devices flying anywhere, from congested urban areas to the most rural zones. The controversial measure by the Federal Aviation Administration, which is subject to public comment and could change before it becomes final, is a key foundation to advance drone-driven commerce, including deliveries of consumer goods by companies such as Alphabet Inc.'s Wing and Amazon.com The rules would come into full force three years after being finalized. "Remote ID technologies will enhance safety and security by allowing the FAA, law enforcement and federal security agencies to identify drones flying in their jurisdiction," Transportation Secretary Elaine Chao said in a press release.

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Rest of Europe 8.4 Asia Pacific 8.4.1

NeurIPS 2019 was with around 13,000 attendees the largest ML conference of the year. The NeurIPS 2019 Program Chairs did a fantastic analysis of the reviewing process. NeurIPS has no free-loader problem: Most of the authors of submitted papers participate in reviewing. It is still unclear how to filter papers before the full review. Review quality (as measured by length) is not lower compared to smaller conferences.

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A simple device, just a heat and movement sensor attached to digital camera, has revolutionised the way that conservationists learn about animals in the wild. Camera traps are a very simple solution to the task of working out when, where and how wildlife interacts with its environment. Monitoring populations without damaging habitats, these relatively simple devices have provided some astonishing finds including revealing species previously hidden in the untouched depths of the forest. Elusive new creatures aren't their only speciality, however, as in 2015, similar devices helped reveal that the critically endangered Javan rhinoceros was breeding and significantly adding to its tiny population. After identifying a likely area for a sighting, usually with the help of local guides, traps are placed at animal height on trees and posts and left to wait until wildlife walks by.

The Brazilian government has taken another step towards the creation of public policies around artificial intelligence (AI). A national AI strategy will be created as a response to the worldwide race for leadership in the field and the need to discuss the future of work, education, tax, research and development as well as ethics as the application of related technologies becomes more pervasive. A public consultation has been launched to gather input around how AI can solve the country's main issues, identify priority areas of focus for the development and use of the technologies, as well as limits for it. According to the summary on the purpose of the consultation, which ends on January 31, 2020, the government understands that AI can bring improvements to the country's competitiveness and productivity, as well as the provision of public services, quality of life and to reduce social inequality in the southern hemisphere's biggest economy. Brazil adheres to the Organisation for Economic Co-operation and Development (OECD)'s human-centred AI Principles, which provide for recommendations around areas such as transparency and explainability.

These and many other fascinating insights are from an analysis of AI startups' funding rounds in 2019 using Crunchbase Pro research. AI startups who have had seed, early-stage venture or late-stage venture funding since December 31, 2018, and are U.S.-based are included in the analysis which is provided here. Crunchbase Pro found 499 startups meeting the search criteria as of today. Their AI strategies include improve every aspect of the customer's lifecycle from pricing through scheduling post-stay cleans. The company manages a growing portfolio of more than 14,000 vacation homes in the U.S, Europe, Central, and South America, and South Africa.