Cheriton School of Computer Science Professor Shai Ben-David, his former PhD student Hassan Ashtiani, now an Assistant Professor at McMaster University, along with colleagues Christopher Liaw, Abbas Mehrabian and Yaniv Plan, have received a best paper award at NeurIPS 2018, the 32ndAnnual Conference on Neural Information Processing Systems.
NeurIPS (formerly NIPS) is the largest and most important annual conference for machine learning. It attracts more than 5,000 paper submissions and many thousands of participants. This year, the conference was held from December 3 to 8, 2018 in Palais des congrès de Montréal, a large convention center in Montréal.
Their paper is titled Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes. Estimating distributions from observed data is a fundamental task in statistics that has been studied for more than a century. This task also arises in applied machine learning and it is common to assume that the distribution can be modelled using a mixture of Gaussians. Read the full story.