The author of the book, 'Pattern Recognition and Machine Learning', is Christopher M. Bishop. The book is about algorithms that allow for quick, approximate answers rather than the exact answer.
Masashi Sugiyama has written: 'Density ratio estimation in machine learning' -- subject(s): COMPUTERS / Computer Vision & Pattern Recognition, Estimation theory, Machine learning
Ramakant Nevatia has written: 'Machine perception' -- subject(s): Pattern recognition systems
Monica D. Fournier has written: 'Perspectives on pattern recognition' -- subject(s): Pattern recognition, Pattern recognition systems
Zoya Shmyr has written: 'Recognition of prior learning (RPL) within the newcomer community' -- subject(s): Immigrants, Education, Recognition of prior learning
Francesco Camastra has written: 'Machine learning for audio, image and video analysis' -- subject(s): Machine learning
Laurenz Wiskott is a German neuroscientist known for his research on computational neuroscience and machine learning. He has published numerous scientific articles on topics such as visual processing in the brain and neural network models for image recognition.
Siddhivinayak Kulkarni has written: 'Machine learning algorithms for problem solving in computational applications' -- subject(s): Machine learning
Sandy E. Mendelson Ages has written: 'The effects of overt verbalization on recognition task with six year old children' -- subject(s): Cognition in children, Learning, Psychology of, Psychology of Learning, Recognition (Psychology), Verbal learning
Satoshi Watanabe has written: 'Pattern recognition' -- subject(s): Pattern perception
Robert Stepp has written: 'Conjunctive conceptual clustering' -- subject(s): Cluster analysis, Data processing, Machine learning, Pattern perception
Hermann Rohrer has written: 'A supervised network of adaptive automata for pattern recognition' -- subject(s): Adaptive control systems, Pattern recognition systems
Anirban DasGupta has written: 'Probability for statistics and machine learning' -- subject(s): Probabilities, Stochastic processes, Mathematical statistics, Machine learning