We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
Motion capture data from human subjects exhibits considerable redundancy. In this paper, we propose novel methods for exploiting this redundancy. In particular, we set out to find...
Guodong Liu, Jingdan Zhang, Wei Wang 0010, Leonard...
Decision-support requires the gathering and presentation of information, but is subject to many kinds of resource restrictions (e.g. cost, length, time). Individual users differ n...
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
We present automated, real-time models built with machine learning algorithms which use videotapes of subjects' faces in conjunction with physiological measurements to predic...
Jeremy N. Bailenson, Emmanuel D. Pontikakis, Iris ...