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Learning in Graphical Models
In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume. Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and...
Driven from Within
'A part of all those people who helped me along the way can be found in everything I have done and continue to do. I had some great teachers - and I listened to what they had to say.' - Michael Jordan A global icon in sports, style and business, Michael Jordan is famous for his unrivalled athletic ability, his fierce determination, and his grace under pressure. In DRIVEN FROM WITHIN, he makes it clear that his phenomenal success is thanks in large part to the teachers, mentors and friends who have guided him throughout his life. Here is a book about the power of collaboration and teamwork, the energy that is released when people share their gifts and hard-won knowledge. With almost two million copies of his three previous books in print, Michael Jordan has proven himself to be as strong a performer in bookstores as he is on the court. Lavishly illustrated and beautifully designed, this is Michael Jordan's most intimate book to date. Organized around the qualities that Jordan demonstrates in his own life and that he looks for in others - qualities like authenticity, integrity, passion and commitment - DRIVEN FROM WITHIN is an inspiring record of an extraordinary life.
Michael Jordan
A kinetic graphic biography about Michael “Air” Jordan, the greatest basketball player of all time and most influential athlete in history, from the creator of the acclaimed and best-selling 21: The Story of Roberto Clemente. This tour-de-force graphic biography explores basketball superstar Michael Jordan’s public successes and private struggles, with Santiago’s passion for his subject shining through on every full-color page. At the age of 19, Jordan scored the winning jump shot in the final seconds of the 1982 NCAA Championship, earning him the moniker “Air.” He was drafted by the Chicago Bulls in 1984, a team with a decade of failure. By 1991, Jordan led the Bulls to their fi...
Graphical Models
This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader...
Dream Big
From the age of nine, Michael dreams of playing basketball for the United States in the Olympics, and with hard work and his mother's encouragement, he realizes his dream. Full color.
I Can't Accept Not Trying
The former basketball player shares his views on achieving excellence, including goals, fears, commitment, teamwork, learning the fundamentals, and leadership
When Nothing Else Matters
As one of the greatest, most celebrated athletes in history, Michael Jordan conquered professional basketball as no one before. Powered by a potent mix of charisma, near superhuman abilities and a ferocious drive to dominate the game, he achieved every award and accolade conceivable before retiring from the Chicago Bulls and taking an executive post with the Washington Wizards. But retirement didn't suit the man who was once king, and at the advanced age of thirty-eight Michael Jordan decided it was time to reclaim the court that was once his. WHEN NOTHING ELSE MATTERS is the definitive account of Jordan's equally spectacular and disastrous return to basketball. Having closely followed Jordan's final two seasons, Michael Leahy draws a fascinating portrait of an intensely complex man hampered by injuries and assaulted by younger players eager to usurp his throne. In this enthralling book Jordan emerges as an ambitious, at times deeply unattractive character with, unsurprisingly, a monstrous ego. WHEN NOTHING ELSE MATTERS is an absorbing portrait not only of one athlete's overriding ambition, but also of a society so in thrall to its sports stars that it is blind to all their faults.
Who Is Michael Jordan?
Grab your Js and hit the court with this Who Was? biography about NBA superstar Michael Jordan. Meet the man who changed the game forever. Michael Jordan has always been competitive--even as a young boy, he fought for attention. His need to be the best made him a star player on his college basketball team and helped him become an NBA legend, both for his skills and his endorsements. His Nike contract for Air Jordan basketball shoes set an unmatched precedent for professional athletes. Author Kirsten Anderson takes readers through each exciting moment, detailing the iconic reverse lay-ups and jump shots of Michael Jordan's storied career. Look for more Who HQ titles: Who Is LeBron James? Who Was Kobe Bryant? Who Is Shaquille O'Neal? Who Is the Man in the Air?: Michael Jordan
Graphical Models, Exponential Families, and Variational Inference
The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.
A Course in Large Sample Theory
A Course in Large Sample Theory is presented in four parts. The first treats basic probabilistic notions, the second features the basic statistical tools for expanding the theory, the third contains special topics as applications of the general theory, and the fourth covers more standard statistical topics. Nearly all topics are covered in their multivariate setting.The book is intended as a first year graduate course in large sample theory for statisticians. It has been used by graduate students in statistics, biostatistics, mathematics, and related fields. Throughout the book there are many examples and exercises with solutions. It is an ideal text for self study.
