We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
We present Task Superscalar, an abstraction of instruction-level out-of-order pipeline that operates at the tasklevel. Like ILP pipelines, which uncover parallelism in a sequential...
Yoav Etsion, Felipe Cabarcas, Alejandro Rico, Alex...
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
This work is concerned with identification of Hammerstein systems whose outputs are measured by quantized sensors. The system consists of a memoryless nonlinearity that is polynomi...
Yanlong Zhao, Ji-Feng Zhang, Le Yi Wang, Gang Geor...
We describe a method for achieving perceptually minimal video distortion over packet-erasure networks using perceptually unequal loss protection (PULP). There are two main ingredie...
Hojin Ha, Jincheol Park, Sanghoon Lee, Alan Conrad...