Search Results - (((((((ant OR antier) OR mind) OR lantier) OR cantor) OR anne) OR halten) OR wanting) algorithms.

Mastering Scala machine learning by Kozlov, Alexander

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Skin in the game : how putting yourself first today will revolutionize health care tomorrow by Hammergren, John

Table of Contents: “…A Thousand Miles of Health Care and the Last Two Feet -- Chapter 1 Unmanaged Care -- Choices for Tomorrow -- Everyone into the Pool -- Quality Service and You -- Chapter 2 From Tree Bark and Roots to Bar Codes and Robots -- Early Days in the Drug Business -- From Bulk Sacks to Gelatin Pills -- Economies of Scale -- The Technological Leap -- Chapter 3 Why We Go to the Hospital Today and Why We Will Go There Less Often in the Future -- Development of the Hospital -- The Complications Set In -- The End Results System -- The Low-Cost, High-Quality Shift -- Changing Hospital Culture -- The Hospital in the Marketplace -- Chapter 4 The Doctor Will See You Now -- Evolution of the American Doctor -- The Golden Age -- Putting the Doc Back on the Team -- Wiring It Together -- The Medical Home -- The Algorithm Will See You Now -- Chapter 5 Accounting for Care -- Warring Impulses -- A Step Back from the Marketplace -- Fixing the Breakdowns -- The Market Mind-Set -- The 65-Year Drop-Off -- The Consumer in Charge -- Getting the Payer-Provider-Consumer System Aligned -- Virtual Health -- Chapter 6 How Technology Is Putting the Patient at the Center of Care -- The Gap -- Fast-Forward -- Personalized Medicine -- Chapter 7The Blueprint for Change -- Resistance to Change -- Designing the Scorecard -- Getting to A -- Applying the Scorecard -- The Leadership Answer -- The Last Two Feet -- Appendix Resources Web Sites Tips and Guidelines for Educating Yourself -- Selecting Your Care -- Understanding the Payer Systems -- Keeping in Good Health -- Terminology -- Useful Web Sites -- Staying Healthy Overseas -- Notes -- References -- Index.…”
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Introduction to graph and hypergraph theory by Voloshin, Vitaly I. (Vitaly Ivanovich), 1954-

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Machine learning with R quick start guide : a beginner's guide to implementing machine learning techniques from scratch using R 3.5 by Pastor Sanz, Iván

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QoS and Energy Management in Cognitive Radio Network : Case Study Approach. by Mishra, Vishram

Table of Contents: “…1.6.1 Channel Selection in CR Based Infrastructure Network1.6.2 Channel Selection in CR Based Ad-hoc Network; 1.7 MAC Protocols for Cognitive Radio Networks; 1.7.1 Random Access Based MAC Scheme; 1.7.2 Time-Slotted Based MAC Scheme; 1.8 Self-coexistence in Cognitive Radio Networks; 1.8.1 Resource Relocation Based Self-coexistence; 1.8.2 Resource Sharing Based Self-coexistence; 1.9 Discussion; References; 2 Cognitive Radio Network- A Review; 2.1 Spectrum Management; 2.1.1 Ant Colony Optimization Based Spectrum Management; 2.1.2 Non-linear Optimization Based Spectrum Management.…”
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Better living through economics

Table of Contents: “…Introduction / John J Siegfried -- Overview: Highlights of the benefits of basic science in economics / Charles R Plott -- Comment / Daniel S Hamermesh -- Comment / Daniel Newlon -- 1: Evolution of emissions trading / Thomas H Tietenberg -- Comment / Wallace E Oates -- 2: Better living through improved price indexes / Michael J Boskin -- Comment / Jerry Hausman -- 3: Economics and the earned income tax credit / Robert A Moffitt -- Comment / V Joseph Hotz -- 4: Trade liberalization and growth in developing countries / Anne O Krueger -- Comment / Douglas A Irwin -- 5: Role of economics in the welfare-to-work reforms of the 1990s / Rebecca M Blank -- Comment / Nancy Folbre -- 6: Better living through monetary economics / John B Taylor -- Comment Laurence H Meyer -- 7: Greatest auction in history / R Preston McAfee, John McMillan, Simon Wilkie -- Comment / Jeremy Bulow -- 8: Air-transportation deregulation / Elizabeth E Bailey -- Comment / Nancy L Rose -- 9: Deferred-acceptance algorithms: history, theory, practice / Alvin E Roth -- Comment / Peter Cramton -- 9: Economics, economists, and antitrust: a tale of growing influence / Lawrence J White -- Comment / Kenneth G Elzinga -- 11: Economics and the all-volunteer military force / Beth J Asch, James C Miller III, John T Warner -- Comment / Walter Y Oi -- 12: Public policy and saving for retirement: the autosave features of the Pension Protection Act of 2006 / John Beshears [and others] -- Comment / Robert J Shiller -- Contributors -- Index.…”
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The Failure of Risk Management : Why It's Broken and How to Fix It. by Hubbard, Douglas W.

Table of Contents: “…: WHY AMBIGUITY DOES NOT OFFSET UNCERTAINTY -- UNINTENDED EFFECTS OF SCALES: WHAT YOU DON'T KNOW CAN HURT YOU -- DIFFERENT BUT SIMILAR-SOUNDING METHODS AND SIMILAR BUT DIFFERENT-SOUNDING METHODS -- NOTES -- CHAPTER 9: Bears, Swans and Other Obstacles to Improved Risk Management -- ALGORITHM AVERSION AND A KEY FALLACY -- ALGORITHMS VERSUS EXPERTS: GENERALIZING THE FINDINGS -- A NOTE ABOUT BLACK SWANS…”
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The cinema of sensations

Table of Contents: “…I Perception, Body and Mind -- Thinking like a Carpet: Embodied Perception and Individuation in Algorithmic Media / Laura U. …”
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Microbiological sensors for the drinking water industry

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Artificial intelligence with Python : build real-world artificial intelligence applications with Python to intelligently interact with the world around you by Joshi, Prateek

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The marketing performance blueprint : strategies and technologies to build and measure business success by Roetzer, Paul, 1978-

Table of Contents: “…Title Page; Copyright; Dedication; Foreword; Acknowledgments; Introduction; Underprepared and Underperforming; Build a Performance-Driven Organization; Accelerate Success; Note; Section I: The Backstory; Chapter 1: Mind the Gaps; The Marketing Talent Gap; The Marketing Technology Gap; The Marketing Strategy Gap; The Marketing Performance Gap; Notes; Chapter 2: Commit to Digital Transformation; Adoption and Adaptation; Obstacles to Evolution; The Exposed Brand; Notes; Section II: Marketing Talent; Chapter 3: Build a Modern Marketing Team; A Talent War Has Begun; Rise of the Hybrids.…”
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Regression Analysis with Python. by Massaron, Luca, Boschetti, Alberto

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Insight into Theoretical and Applied Informatics : Introduction to Information Technologies and Computer Science. by Yatsko, Andrzej

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Applied Artificial Intelligence : Proceedings of the 7th International FLINS Conference. by Arena, Paolo, Fortuna, Luigi

Table of Contents: “…An extended branch-and-bound algorithm for fuzzy linear bilevel programming / G. …”
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Machine Learning for OpenCV. by Beyeler, Michael

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Work and Stress : A Research Overview. by Dewe, Philip

Table of Contents: “…Mindful use of technology -- Other technologies and their context -- The requirement for new leadership styles -- Emerging technologies -- Cognitive technology: AI -- artificial intelligence and machine learning -- A pause to catch our breath and think about what this means for work stress research -- Turning back to other emerging technologies: augmented reality (AR) and algorithms -- Internet of things, wearables and smart clothing -- Conclusion: an industry at risk? …”
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Large Scale Network-Centric Distributed Systems

Table of Contents: “…2.4.2 Algorithmic Recognizer Add-on2.4.3 Source Code Transformer for GPUs; 2.5 Conclusion; References; 3 A Multithreaded Branch-and-Bound Algorithm for Solving the Flow-Shop Problem on a Multicore Environment; 3.1 Introduction; 3.2 Flow-Shop Scheduling Problem; 3.3 Parallel Branch-and-Bound Algorithms; 3.3.1 Multiparametric Parallel Model; 3.3.2 Parallel Tree Exploration Model; 3.3.3 Parallel Evaluation of Bounds; 3.3.4 Parallel Evaluation of a Bound Model; 3.4 A Multithreaded Branch-and-Bound; 3.4.1 Low-Level Multithreaded B & B; 3.4.2 High-Level Multithreaded B & B.…”
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Rediscovering mathematics : you do the math by Simonson, Shai

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Debates in the digital humanities 2016

Table of Contents: “…Father Busa Female Punch Card Operatives / Melissa Terras and Julianne Nyhan -- On the Origin of "Hack" and "Yack" / Bethany Nowviskie -- Reflections on a Movement: #transformDH, Growing Up / Moya Bailey, Anne Cong-Huyen, Alexis Lothian, and Amanda Phillips.…”
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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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