A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows …-known algorithm of Glover, and checked for non-negativity. The first non-negative point is an optimal solution of (GP). Advantages and … disadvantages of the algorithm are discussed; in particular, the implementation of the algorithm (which can be easily extended so as …

algorithm herself, her equity preference has no effect on the training procedure. So long as the data, however biased, contain … signal, they will be used and the learning algorithm will be the same. Equity preferences alone provide no reason to alter …

thinking may be important. Our results suggest that information-processing heuristics may be important even in markets with …

modern behavioral economics. This chapter reviews theory and evidence on this topic, with the goal of facilitating more … processes, biases in belief updating, the representativeness heuristic as a possible unifying theory, and interactions between …

expectations with less naïve learning rules. Our results suggest that fast and frugal robust heuristics may not be a second …

structure is relevant in many applications. We develop the theory underlying optimal menus of non-linear schedules and prove …

We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection … support of the ergodic measure roughly uniformly. The proposed algorithm is tractable in problems with high dimensionality …

volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves … set of preferences than the single variable that the algorithm focuses on; for instance, judges may care about racial … well. In addition, by focusing the algorithm on predicting judges' decisions, rather than defendant behavior, we gain some …