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Jul 4, 2018 at 12:00 UTC |Updated Jul 4, 2018 at 12:10 UTC

An EU banking regulator has published a new report exploring the benefits and risks associated with the use of distributed ledger technology (DLT) in finance.

In a report published on Tuesday that discusses the rising trend of financial technology, the European Banking Authority (EBA) highlighted two banking-related use cases of blockchain: cross-border trade finance and identity authentication.

With a detailed explanation of how smart contracts and DLT can be utilized in the case of cross-border transactions, the EBA says the nascent technology can help solve a variety of issues. The paper's authors wrote:

That said, the EBA also noted the emerging technology still faces potential risks as applicable law remains uncertain at the moment. As such, conflict of interests may occur among DLT nodes that are located in different jurisdictions.

The EBA went on to explain:

The EBA's comment notably follows news that a group of European banks has BZEES Zsa Zsa Ribbed Wedge Sneaker baZ8D
a series of live cross-border trades using a jointly-developed blockchain platform.Those firms have said they want to expand the platform to elsewhere in the region.

Elsewhere in the report, the banking regulator also said that DLT can potentially streamline the ID verification process in European banks' customer due diligence since data can be shared in a distributed network.

However, the EBA said one of the unresolved questions in the application is how to ensure each party on a DLT network conducts a comprehensive due diligence process so that incomplete or invalid data will not be shared among different nodes.

"A number of opportunities emerge from the use of DLT and smart contracts for trade finance. The most promising are the potential efficiency gains, cost reduction, and lower risk of duplicate financing and loss or manipulation of documents."

"For example, a digitally signed contract might not be enforceable in all the jurisdictions. It is essential to establish the applicable jurisdiction, in case of conflict, and the dispute mechanisms, when a dispute arises. "

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NIPS 2018 Competition Track

This is the second NIPS edition on "NIPS Competitions". We received 21 competition proposals related to data-driven and live competitions on different aspects of NIPS. Proposals were reviewed by several high qualified researchers and experts in challenges organization. Eight top-scored competitions were accepted to be run and present their results during the NIPS 2018 Competition track days. Evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and managing procedure. Below, you can find the eight accepted competitions. Please visit each competition webpage to read more about the competition, its schedule, and how to participate. Each competition has its own schedule defined by its organizers. The results of the competitions, including organizers and top ranked participants talks will be presented during the 2 Competition track days at NIPS 2018. Organizers and participants will be invited to submit their contribution as a book chapter to the upcoming NIPS 2018 Competition book, within Springer Series in Challenges in Machine Learning.

Eight top-scored competitions were accepted

More details below!

Competition summary: In many real-world machine learning applications, AutoML is strongly needed due to the limited machine learning expertise of developers. Moreover, batches of data in many real-world applications may be arriving daily, weekly, monthly, or yearly, for instance, and the data distributions are changing relatively slowly over time. This presents a continuous learning, or Lifelong Machine Learning challenge for an AutoML system. Typical learning problems of this kind include customer relationship management, on-line advertising, recommendation, sentiment analysis, fraud detection, spam filtering, transportation monitoring, econometrics, patient monitoring, climate monitoring, and manufacturing and so on. In this competition, which we are calling AutoML for Lifelong Machine Learning , large scale datasets collected from some of these real-world applications will be used. Compared with previous AutoML competitions( http://automl.chalearn.org/ ), the focus of this competition is on drifting concepts, getting away from the simpler i.i.d. cases. Participants are invited to design a computer program capable of autonomously (without any human intervention) developing predictive models that are trained and evaluated in a in lifelong machine learning setting.

Competition summary:

Organizers :

Organizers
Wei-Wei Tu, 4Paradigm Inc., China, [email protected]
Hugo Jair Escalante, INAOE (Mexico), ChaLearn (USA),
Isabelle Guyon, UPSud/INRIA Univ. Paris-Saclay, France ChaLearn, USA,
Evelyne Viegas, Microsoft, USA,
Yuqiang Chen, 4Paradigm Inc., China, [email protected]
Qiang Yang, 4Paradigm Inc., China, Johnston amp; MurphyElaine Perfed tYIzD1v

In the past decades, major improvements have been achieved in the treatment of advanced non-small cell lung cancer (NSCLC), and the role of chemotherapy in this setting has been definitely established. The current standard treatment for patients with good performance status includes first-line treatment with a platinum-based two-drug regimen (doublet) for a maximum of six cycles in the absence of unacceptable toxicity or progressive disease [ Frye Tabitha Harness Tall w3g1G1vIbY
]. However, despite the introduction of new, active agents (gemcitabine, taxanes, vinorelbine, irinotecan, pemetrexed), the prognosis of advanced NSCLC patients is still dismal, with first-line chemotherapy response rates usually in the range of 20%–40% and with a median survival time of approximately 8 months [ 1 ]. In patients with progressive disease after first-line chemotherapy and good performance status, a second-line treatment with single-agent docetaxel is recommended [ 1 ]. A recent phase III trial demonstrated pemetrexed to be as effective as docetaxel in this setting, with a more favorable toxicity profile [ 2 ]. However, the response rate to second-line chemotherapy, either docetaxel or pemetrexed, is <10%.

Several attempts have been made to improve the efficacy of first-line chemotherapy. In trials focusing on the role of cisplatin, none of the non–platinum-containing regimens has been proven to be superior [ 1 ]. Other trials have shown no advantage for three-drug (triplet) versus two-drug combinations in terms of survival, with worse toxicities when a triplet is used [ 3 ]. Finally, studies investigating the optimal treatment duration have demonstrated that prolonged treatment is not beneficial, suggesting that the maximum benefit of chemotherapy is yielded by the first few cycles [ 1 ].

Among new molecular targeted therapies, two orally active inhibitors of the epidermal growth factor receptor tyrosine kinase, namely, gefitinib and erlotinib, have been proven to be active as single agents in second- and third-line treatment [ 1 ]. However, no advantage has been observed from adding one of these agents to a platinum-based doublet [ 4 ]. The addition of bevacizumab, a monoclonal antibody against vascular endothelial growth factor, to standard first-line chemotherapy has improved survival in patients with advanced nonsquamous NSCLC [ 5 ].

Recently, alternative designs of treatment schedules other than combination chemotherapy have been proposed, such as sequential, alternating, maintenance, and consolidation chemotherapy. The feasibility of these approaches in lung cancer patients has been timely demonstrated. This review summarizes the rationale, current data, and perspectives of sequential, alternating, consolidation, and maintenance chemotherapy in patients with advanced NSCLC.

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