In the present paper, we study the problem of aggregation under the squared loss in the model of regression with deterministic design. We obtain sharp oracle inequalities for conve...
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
This paper solves an important problem left open in the literature by showing that U-shapes are unnecessary in iterative learning. A U-shape occurs when a learner first learns, t...
We present a framework for margin based active learning of linear separators. We instantiate it for a few important cases, some of which have been previously considered in the lite...
Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang
Abstract. Considering one-dimensional continuum-armed bandit problems, we propose an improvement of an algorithm of Kleinberg and a new set of conditions which give rise to improve...
Abstract. We propose simple randomized strategies for sequential prediction under imperfect monitoring, that is, when the forecaster does not have access to the past outcomes but r...