Event Location: NSH 1507Abstract: We propose a novel formulation for component analysis that allows for rich instance-level constraints that encourage semantic interpretability of the learned components. Even with simple features and intuitive spatial consistency priors, our method produces accurate, semantically-meaningful image segmentations both with and without supervision.

Event Location: NSH 1507Bio: I am a PhD student at Language Technology Institute, Carnegie Mellon University, from fall 2012. I am working with Prof. Abhinav Gupta on joint learning with language and vision and life-long learning. I am also working with Prof. Tom Mitchell in CMU. Recently, I just finished my internship in MSR with [...]

Event Location: NSH 1507Bio: I'm a sixth year PhD Student in the Machine Learning Department at CMU, working with Alyosha Efros and Abhinav Gupta. I graduated from CMU in 2010 with a B.S. in computer science and cognitive science, with a minor in neural computation, completing an undergraduate thesis with Tai Sing Lee. I'm interested [...]

Event Location: NSH 1507Bio: I am a Ph.D. student in the Robotics Institute at Carnegie Mellon University, under the supervision of Yaser Sheikh. During summer 2015, I interned at Disney Research Zurich where I worked with Thabo Beeler and Derek Bradley. Before joining CMU, I spent three years as a researcher at ETRI, a government-funded [...]