Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
We address the challenge of semantic gap reduction for image retrieval through an improved SVM-based active relevance feedback framework, together with a hybrid visual and concept...
We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classificati...
Nikita Orlov, Lior Shamir, Tomasz J. Macura, Josia...
Interactive configuration guides a user searching through a large combinatorial space of solutions to a system of constraints. We investigate a class of very expressive underlying...
Erik Roland van der Meer, Andrzej Wasowski, Henrik...
The current standard for intra-domain network routing, Open Shortest Path First (OSPF), suffers from a number of problems--the tunable parameters (the weights) are hard to optimiz...
Jessica H. Fong, Anna C. Gilbert, Sampath Kannan, ...