In many real-world auctions, a bidder does not know her exact value for an item, but can perform costly deliberation to reduce uncertainty. Relatively little is known about such deliberative environments, which are fundamentally different from classical auction environments. this paper, we propose new approach that allows us leverage revenue-maximization results in particular, use Myerson (1981...

We survey the fastest known algorithms for learning various expressive classes of Boolean functions in the Probably Approximately Correct (PAC) learning model.

We consider PAC learning of probability distributions (a.k.a. density estimation), where we are given an i.i.d. sample generated from an unknown target distribution, and want to output a distribution that is close to the target in total variation distance. Let F be an arbitrary class of probability distributions, and let F denote the class of k-mixtures of elements of F . Assuming the existence...

This paper applies the theory of Probably Approximately Correct (PAC) learning to multiple output feedforward threshold networks in which the weights conform to certain equivalences. It is shown that the sample size for reliable learning can be bounded above by a formula similar to that required for single output networks with no equivalences. The best previously obtained bounds are improved fo...

This study provides a survey of phenomena that present themselves during moments of naturally occurring inner experience. In our previous studies using Descriptive Experience Sampling (DES) we have discovered five frequently occurring phenomena--inner speech, inner seeing, unsymbolized thinking, feelings, and sensory awareness. Here we quantify the relative frequency of these phenomena. We used...

Inner and outer hair cells were mechanically isolated from the guinea pig cochlea and subjected to stimuli known to induce shape changes in outer hair cells. Depolarization by 70 mM KCl which causes osmotic swelling of outer hair cells also swelled inner hair cells by approximately 8% of their volume. The application of the calcium ionophore ionomycin which induces cortical contractions and elo...

A satisscing search problem consists of a set of probabilistic experiments to be performed in some order, seeking a satisfying connguration of successes and failures. The expected cost of the search depends both on the success probabilities of the individual experiments, and on the search strategy, which speciies the order in which the experiments are to be performed. A strategy that minimizes ...

Submodular function maximization finds application in a variety of real-world decision-making problems. However, most existing methods, based on greedy maximization, assume it is computationally feasible to evaluate F , the function being maximized. Unfortunately, in many realistic settings F is too expensive to evaluate exactly even once. We present probably approximately correct greedy maximi...

To facilitate the testing of models for the evolution of languages, the present note offers a set of linguistic features that are approximately independent of each other. To find these features, the adjusted Rand index (R) is used to estimate the degree of pairwise relationship among 130 linguistic features in a large published database. Many of the R values prove to be near 0, as predicted for...

A* is a best-first search algorithm that returns an optimal solution. w-admissible algorithms guarantee that the returned solution is no larger than w times the optimal solution. In this paper we introduce a generalization of the w-admissibility concept that we call PAC search, which is inspired by the PAC learning framework in Machine Learning. The task of a PAC search algorithm is to find a s...