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The ... ASTD Training & Performance Sourcebook

This title draws on the expertise of top-flight trainers and consultants to present a comprehensive toolkit of the best training activities, group learning exercises, assessment instruments, handouts, and other essential guides for today's busy training and performance professional. The sourcebook offers fully reproducible tools contained on the accompanying CD-ROM.

The ... ASTD Team & Organization Development Sourcebook

This book presents a comprehensive toolkit of the most important topics facing organizations today including managing change, launching organizational initiatives, facilitating teams, goal setting and planning, creative problem solving, building cooperation and trust, and team development.

Inspiring Active Learning

A Complete Handbook for Today's Teachers

How can we structure class time efficiently? How can we explain and lecture effectively? How can we help students master content? How can we make learning more real and lasting? In this revised and greatly expanded 2nd edition of Inspiring Active Learning, educators Merrill Harmin and Melanie Toth provide answers to our fundamental teaching questions and show us how to transform our classrooms into communities of active, responsible learners. The authors present an array of research-based, teacher-tested strategies for managing our everyday responsibilities--from beginning a class to grading homework, from instructing large groups to promoting diligent seatwork, from motivating slackers to handling disrupters. These strategies focus on mutual respect, not bossiness; collaboration, not isolation; commitment to learning, not fear of failure; and the dignity of all, not praise or rewards for a few. Regardless of our level of experience or the grade or subject we teach, the active-learning approach helps us * Perform routine teaching tasks more easily. * Discover a higher level of teaching success and personal satisfaction. * Establish a class climate of full participation and cooperation. * Prepare engaging lessons that keep students productively involved. * Encourage students to work energetically, willingly, and intelligently each day. * Inspire all students, even the most challenging, to strive for excellence. With its detailed classroom examples and more than 250 practical strategies, Inspiring Active Learning is a comprehensive reference for solving almost any teaching problem.

Learning. 3. One of the everyday tasks of teachers is planning lessons that
inspire all students to stay actively, productively involved. Or, to be more specific,
we might say the goal is to craft lessons that inspire students to work with high
dignity, ...

Data Analysis, Machine Learning and Knowledge Discovery

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012. ​

Metod potencialnych funkcij v teorii obucenia mashin (The method of potential
functions in machine learning theory) [in Russian]. Moscow: Nauka. Hastie, T.,
Tibshirani, R., & Friedman, J. H. (2009). The elements of statistical learning: Data
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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

21. 22. 23. 24. 2. Abe, N., Mamitsuka, H.: Query learning strategies using
boosting and bagging. In: Proc. of ICML 1998, pp. 1–10 (1998) 3. Donmez, P.,
Carbonell, J.G.: Optimizing estimated loss reduction for active sampling in rank
learning.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.

0 0.5 1 1.5 2 2.5 3 3.5 Online Q-learning vs Always On Q-learning (Online)
Always On 0 20 40 60 80 100 120 140 A v e r a g e d a i l y c o s t ( E u r o ) Time (
Days) Fig. 2. Online Q-learning vs “Always on” control Offline Q-learning Comfort
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