We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed t...
Abstract—This work proposes a novel approach - personalized forecasting - to take into account the sequential effect in predicting student performance (PSP). Instead of using all...
Given a known protein sequence, predicting its secondary structure can help understand its three-dimensional (tertiary) structure, i.e., the folding. In this paper, we present an ...
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
Auction mechanism design has traditionally been a largely analytic process, relying on assumptions such as fully rational bidders. In practice, however, bidders often exhibit unkn...
David Pardoe, Peter Stone, Maytal Saar-Tsechansky,...