It really is sad to lose such a great mind and, as many have echoed here, a great personality. We are all thinking of you. Because of that, he is easily remembered and will be greatly missed. I am just a student of Machine Learning from Indonesia. Both methods use the idea of learning a function that maps datapoints into a space in which semantically similar objects are nearby, while semantically dissimilar objects are far apart. His energy and his glow as Zoubin rightly put it , along with his humor was incredibly infectious and it really crossed all boundaries. He was one of the most gifted educators I have ever had the privilege of knowing, and as his peers here well know, his research record is one of distinction.
Truly an incredible mind and athlete. May his soul rest in peace. His talks and discussions were clear and highly entertaining. Sam was an amazingly generous friend and truly inspiring colleague. Announcements , Machine Learning — jl 7:
Linguistic theories and substantial psychophysical evidence argue strongly that articulatory model inversion plays an important role in speech perception and recognition in the brain.
Because such generative models capture information about the set of possible observations, they can help to explain complex variability naturally present in the data and are useful in separating signal from noise.
And yet your life is full of joyful times, too. I was with him when his mom died, also tragically young, from leukemia. It spurred an entire new eam of machine learning, called manifold learning, and gathered a considerable amount of interest from other technical fields, including applied mathematics.
Sam published a set of papers on speech and signal analysis, particularly using factorial HMM and hierarchical models. His energy and his glow as Zoubin rightly put italong with his humor was incredibly infectious and it really crossed all boundaries.
My heart aches from this sorrowful goodbye.
Sam Roweis died « Machine Learning (Theory)
But I saw few of his lectures from http: I just wanted to express my deepest condolences… this is very sad indeed. Roweis, I had watched the videos of his teaching Machine Learning many times, and I admire him as a leading researcher in this field. There was so much positive energy and enthusiasm in his talks, I cannot bring myself to believe this… My thoughts and prayers are with his family.
Abstract When difficult computations are to be performed on sensory data it is often advantageous to employ a model of the underlying process which produced the observations. Sam inspired many students to pursue a career in research, and to focus their research on machine learning and artificial intelligence.
Data driven production models for speech processing
Unfortunately, despite potential engineering advantages and evidence for being part of the human strategy, such inversion of speech production models is absent in almost all artificial speech processing systems. Sam’s stay at Google, and the success roweiss his computational astronomy work, had renewed his interest in academic research. He proposed a variation of the well-established Hidden Markov Model HMM method for speech recognition, and he showed how a new form of Independent Component Analysis ICA could be used to separate multiple audio sources from a single microphone signal.
Sam eoweis an extended paternity leave from Google to take care of the twins. I never met Sam but learned quite a lot from his work.
The machine learning community has lost one of its best and most generous. The world will be much dimmer without him; this is such an unbelievable loss.
Sam was an amazing individual. Sam had a singular gift: Sam was a dear friend of our family and we are all so, so sad. Data driven production models for speech processing Citation Roweis, Sam T. Sam was a wonderful teacher, with a great ability to combine the practical, the theoretical, the serious, the funny, the ability to think around problems, and the ability to go straight through them. SNE has become a popular method for visualizing and organizing high-dimensional data, while NCA has spurred a resurgence of interest in methods that learn similarity metrics from data.
A Caltech Library Service. These inferred states can then be used as inputs to a pattern recognition or pattern completion module.
I feel really lucky to have collaborated with him. I had the privilege of taking two courses with him, and even now find myself occasionally referring to his course notes. Sam was not just a scientist, however, he was also an engineer. Very sorry to hear this.
Sam Roweis, Associate Professor
He was very approachable and friendly. I knew Sam as a teacher and a mentor as an undergraduate at Toronto. Both methods use the idea of learning a function that maps datapoints into a space in which semantically similar objects are nearby, while semantically dissimilar objects are far apart.