It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
An active learner has a collection of data points, each with a label that is initially hidden but can be obtained at some cost. Without spending too much, it wishes to find a cla...
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
In this work, we improve on existing work that studied the relationship between the proof system of modern SAT solvers and general resolution. Previous contributions such as those ...
Abstract. We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically, knowledge of effective term weights on ...