{"title":"Sheng Li","description":null,"products":[{"product_id":"machine-learning-for-causal-inference-book-sheng-li-9783031350504","title":"Machine Learning for Causal Inference","description":"This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference, which include basic definitions, illustrative examples, and assumptions. It then delves into the different types of classical causal inference methods, such as matching, weighting, tree-based models, and more. Additionally, the book explores how machine learning can be used for causal effect estimation based on representation learning and graph learning. The contribution of causal inference in creating trustworthy machine learning systems to accomplish diversity, non-discrimination and fairness, transparency and explainability, generalization and robustness, and more is also discussed. The book also provides practical applications of causal inference in various domains such as natural language processing, recommender systems, computer vision, time series forecasting, and continual learning. Each chapter of the book is written by leading researchers in their respective fields.\u003cp\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003ci\u003eMachine Learning for Causal Inference\u003c\/i\u003e explores the challenges associated with the relationship between machine learning and causal inference, such as biased estimates of causal effects, untrustworthy models, and complicated applications in other artificial intelligence domains. However, it also presents potential solutions to these issues. The book is a valuable resource for researchers, teachers, practitioners, and students interested in these fields. It provides insights into how combining machine learning and causal inference can improve the system's capability to accomplish causal artificial intelligence based on data. The book showcases promising research directions and emphasizes the importance of understanding the causal relationship to construct different machine-learning models from data.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51061189476625,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51061192884497,"sku":"NIN9783031350504","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52334454178065,"sku":"NLS9783031350504","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/3031350502.jpg?v=1766140906"},{"product_id":"neue-eu-spielzeugrichtlinie-und-deren-auswirkung-auf-chinesische-hersteller-book-sheng-li-9783842893214","title":"Die neue EU-Spielzeugrichtlinie und deren Auswirkung auf Chinesische Hersteller","description":"Mit der seit Juli 2011 gultigen EU-Spielzeugrichtlinie 2009\/48\/EG mussen sich Spielzeuge, die auf den europaischen Markt gebracht werden mochten, den weltweit strengsten Sicherheitsvorgaben unterziehen. Es ist absehbar, dass auch in Zukunft die Tendenz der stetigen Verscharfung der Spielzeugsicherheit in Europa zunehmen und nicht abnehmen wird. Obwohl diese Richtlinie lediglich an die EU-Mitgliedstaaten gerichtet ist, wirkt sie sich unweigerlich auf die chinesische Spielzeugindustrie aus, die allein im Jahr 2010, 86% der gesamten Importmenge von Spielzeug nach Europa produziert hat. Das Ziel der vorliegenden Studie liegt darin, dem Leser zu ermoglichen, das neue EU-Spielzeugsicherheitsrecht aus dem Blickwinkel der chinesischen Spielzeugunternehmen zu betrachten. Der Umfang und der Inhalt der Herstellerpflichten bilden den Hauptschwerpunkt dieser Studie. Die behordliche Markuberwachung, die im Umkehrschluss eine Reihe von Duldungs-, Unterstutzungs- und Auskunftspflichten fur chinesische Spielzeugunternehmen zur Folge hat, wird unter die Lupe genommen, um zu untersuchen, wo die Grenzen der Marktuberwachungskompetenz aus verwaltungsverfahrensrechtlicher Sicht liegen. Zuletzt bietet die Studie einen Einblick in die aktuelle Situation der chinesischen Produzenten in der globalisierten Spielzeugindustrie.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51224459641105,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51224461836561,"sku":"NIN9783842893214","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52679165214993,"sku":"NLS9783842893214","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/3842893213.jpg?v=1750968173"},{"product_id":"vergleich-der-deutschen-und-chinesischen-arbeitsrechte-book-sheng-li-9783956367823","title":"Ein Vergleich der deutschen und chinesischen Arbeitsrechte","description":"W hrend das moderne Arbeitsrecht in Deutschland das Ergebnis einer hundertj hrigen Entwicklung darstellt, ist das Arbeitsrecht heutzutage ebenfalls ein wichtiger Bestandteil des chinesischen Wirtschaftslebens geworden und gewinnt es immer mehr an gesellschaftliche Bedeutung. Nach drei igj hrigem Wirtschaftswachstum befindet sich China derzeit am Wendepunkt von ausschlie licher Betonung der wirtschaftlichen Effizienz zur Anstrebung mehr sozialer Gerechtigkeit im Rahmen der harmonischen Gesellschaft. Vor dem Hintergrund der wirtschafts- und sozialpolitischen Reformen zeichnet sich ab, dass ein verl ssliches Arbeitsrecht vom chinesischen Gesetzgeber bereits als eine unabdingbare Voraussetzung f r die nachhaltige Entwicklung Chinas angesehen ist. Anderseits soll man aber nicht  bersehen, dass das Arbeitsrecht nicht nur ein Teil der Sozialpolitik ist, sondern auch sich eng mit der Wirtschaftspolitik zusammenh ngt. Aus diesem Grund hat China ein rechtes Ma  f r Arbeitnehmerschutz zwischen der Privatautonomie und staatlicher Einflussnahme zu finden. Dabei stellen sich selbstverst ndlich die folgenden Fragen: Ist es  berhaupt realistisch, dass China noch als ein Entwicklungsland die Arbeitnehmerrechte in gleichem Ma e wie Deutschland durch Arbeitsrecht sch tzt? Wie ist die arbeitsrechtliche Lage in China? Wie gro  ist der R ckstand des chinesischen Arbeitsrechts gegen ber dem deutschen Arbeitsrecht? Die Aufgabe der Arbeit besteht daher darin, die arbeitsrechtlichen Lagen beider L nder miteinander gegen berzustellen und damit die positiven Entwicklungen und Missst nde der chinesischen Arbeitsrechte zu identifizieren. Der Vergleich erfolgt in vierlei Hinsicht. Im Grundlagenteil(2) wird zun chst ein Makrovergleich  ber die Rahmenbedingungen der deutschen und chinesischen Arbeitsm rkte durchgef hrt. Dabei sollen auch die Rechtsquelle des Arbeitrechts, Arbeitsgerichtsbarkeit und zust ndige Arbeitsbeh rden beider L nder dargestellt werden. Anschlie end werden im Teil der Indiv","brand":"WoB","offers":[{"title":"- \/ - \/ INTERNAL","offer_id":52408011030801,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52408011620625,"sku":"NLS9783956367823","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783956367823.jpg?v=1758773767"},{"product_id":"machine-learning-for-causal-inference-book-sheng-li-9783031350535","title":"Machine Learning for Causal Inference","description":"This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference, which include basic definitions, illustrative examples, and assumptions. It then delves into the different types of classical causal inference methods, such as matching, weighting, tree-based models, and more. Additionally, the book explores how machine learning can be used for causal effect estimation based on representation learning and graph learning. The contribution of causal inference in creating trustworthy machine learning systems to accomplish diversity, non-discrimination and fairness, transparency and explainability, generalization and robustness, and more is also discussed. The book also provides practical applications of causal inference in various domains such as natural language processing, recommender systems, computer vision, time series forecasting, and continual learning. Each chapter of the book is written by leading researchers in their respective fields.\u003cp\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003ci\u003eMachine Learning for Causal Inference\u003c\/i\u003e explores the challenges associated with the relationship between machine learning and causal inference, such as biased estimates of causal effects, untrustworthy models, and complicated applications in other artificial intelligence domains. However, it also presents potential solutions to these issues. The book is a valuable resource for researchers, teachers, practitioners, and students interested in these fields. It provides insights into how combining machine learning and causal inference can improve the system's capability to accomplish causal artificial intelligence based on data. The book showcases promising research directions and emphasizes the importance of understanding the causal relationship to construct different machine-learning models from data.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"- \/ - \/ INTERNAL","offer_id":52418643919121,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ GARDNERS","offer_id":52418644803857,"sku":"NGR9783031350535","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783031350535.jpg?v=1785953152"},{"product_id":"robust-representation-for-data-analytics-book-sheng-li-9783319867960","title":"Robust Representation for Data Analytics","description":"This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary.\u003cp\u003eLeveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. \u003ci\u003eRobust Representations for Data Analytics\u003c\/i\u003e covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.\u003c\/p\u003e","brand":"WoB","offers":[{"title":"- \/ - \/ INTERNAL","offer_id":52500682604817,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ GARDNERS","offer_id":52500683424017,"sku":"NGR9783319867960","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783319867960.jpg?v=1786088043"},{"product_id":"chinese-computational-linguistics-book-sheng-li-9783030841850","title":"Chinese Computational Linguistics","description":"This book constitutes the proceedings of the 20th China National Conference on Computational Linguistics, CCL 2021, held in Hohhot, China, in August 2021.\u003cp\u003eThe 31 full presented in this volume were carefully reviewed and selected from 90 submissions.\u003c\/p\u003e\n\n\u003cp\u003eThe conference papers covers the following topics such as Machine Translation and Multilingual Information Processing, Minority Language Information Processing, Social Computing and Sentiment Analysis, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications. \u003c\/p\u003e","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52613582192913,"sku":"NLS9783030841850","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783030841850.jpg?v=1786614731"}],"url":"https:\/\/www.worldofbooks.com\/en-gb\/collections\/author-books-by-sheng-li.oembed","provider":"World of Books ","version":"1.0","type":"link"}