We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
Distributional similarity is a classic technique for entity set expansion, where the system is given a set of seed entities of a particular class, and is asked to expand the set u...
We present a novel approach for verifying safety properties of finite state machines communicating over unbounded FIFO channels that is based on applying machine learning techniqu...
Abhay Vardhan, Koushik Sen, Mahesh Viswanathan, Gu...