摘要: 連假開始,你的論文存貨還夠嗎?對人工智慧感興趣的你,是否還停留在碎片閱讀階段?想要進行更深一步的學習,本篇推文中網羅了人工智慧領域15篇精選論文,讓你及時了解AI學科前沿成果。

摘要: 11節 麻省理工學院 的通用人工智慧課程。講師陣容超豪華:谷歌技術總監Kurzweil、特斯拉AI總監Andrej Karpathy、波士頓動力CEO Marc Raibert、OpenAI的聯合創始人Ilya Sutskever等。課程內容包括:通用人工智慧、計算認識科學、認知建模、深度學習等。文中附有課程講義下載和課程視頻地址。

摘要: 「贏者詛咒」:贏得拍賣品的中標者出價高於其他競標者,但他很可能對拍賣品估價過高,支付了超過其價值的價格,從而贏得的拍賣品的收益會低於正常收益甚至爲負。換句話說,就是當你一心想要贏得競標時,卻偏離了你原本的目的:當我們爲各種測評任務中取得的分數歡欣鼓舞時,可能我們已經受到了「贏者詛咒」。

圖名

Big data has both high volume and high velocity – one way this manifests is as silos of in-situ data representing departments in banks that are very difficult to move and integrate to obtain a single coherent customer view. Further, the ability to perform data analytics – dynamically and in near real-time – of rapidly changing customer and market data is increasingly critical for competitiveness. By considering the distributed nature of financial data storage and the velocity of financial markets, the objective of this RP is to develop distributed and real-time machine learning methods to identify decentralised and dynamic models for financial analysis, prediction, and risk management.

This project will develop (i) methods to identify cross-effects between different data resources, regions, sectors, and markets, (ii) distributed versions of methods to identify decentralised models that include individual local model components learned from local resources and cross-impact model components learned from data resources in other regions/sectors/markets, and (iii) real-time learning methods to update decentralised models and address financial market velocity.

Based on the distributed and cloud computing infrastructure, this approach should address the weakness of existing data-centralised and off-line machine learning methods, which fail to consider the cost of data transportation, storage, and fast timevarying characteristics of financial markets. The originality of this approach is its dynamic integration, by distributed and real-time mining, to maximise the effectiveness and efficiency of big data analysis.

Early Stage Resercher working on the project: Sergio Garcia Vega

Supervisor: Professor John Keane, University of Manchester / john.keane(at)manchester.ac.uk

轉貼自: Finance BigData.eu

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