Adam Shwartz

The gender achievement gap in higher STEM education is well documented as STEM course grades often show a bias favoring men, even when controlling for overall student achievements. The current work, which was preregistered prior to data collection, replicates and extends prior work to evaluate several possible contributors to the gender gap in advanced STEM courses. The contributing factors include students’ STEM-preparedness, learning assessment design, and students’ activity level in the course. We analyzed the data of a cohort of 315 undergraduate engineering students in a leading technological university in Israel. A mixed-effect model analysis revealed a gender gap in both high-stakes and low-stakes assessments of learning. We found that the gap first appears in lower-division undergraduate mathematics courses and remains steady through advanced STEM courses, with relatively little variance between different courses. We further found that students’ activity in the course’s learning management system is not associated with a gap reduction. The analysis suggests that the gender gap can be traced back, at least in part, to students’ STEM-preparedness when entering college. Notably, although the gap is traced prior to college, high-school grades likely show a ceiling effect and are thus not representative of the gap shown later in college. Therefore, it may be that other preparatory factors contribute to this gap, outside of or in addition to high-school performance.

On the risk-sensitive cost for a Markovian multiclass queue with priority

The paper has two objectives. The first is to study rigorously the transient behavior of some peer-to-peer (P2P) networks whenever information is replicated and disseminated according to epidemic-like dynamics. The second is to use the insight gained from the previous analysis in order to predict how efficient are measures taken against P2P networks. We first introduce a stochastic model that extends a classical epidemic model and characterize the P2P swarm behavior in presence of free-riding peers. We then study a second model in which a peer initiates a contact with another peer chosen randomly. In both cases, the network is shown to exhibit phase transitions: A small change in the parameters causes a large change in the behavior of the network. We show, in particular, how phase transitions affect measures of content providers against P2P networks that distribute nonauthorized music, books, or articles and what is the efficiency of countermeasures. In addition, our analytical framework can be generalized to characterize the heterogeneity of cooperative peers.

Ergodic control for discrete time controlled Markov chains with a locally compact state space and a compact action space is considered under suitable stability, irreducibility, and Feller continuity conditions. A flexible family of controls, called action time sharing (ATS) policies, associated with a given continuous stationary Markov control, is introduced. It is shown that the long-term average cost for such a control policy, for a broad range of one-stage cost functions, is the same as that for the associated stationary Markov policy. In addition, ATS policies are well suited for a range of estimation, information collection, and adaptive control goals. To illustrate the possibilities we present two examples. The first demonstrates a construction of an ATS policy that leads to consistent estimators for unknown model parameters while producing the desired long-term average cost value. The second example considers a setting where the target stationary Markov control q is not known but there are sampling schemes available that allow for consistent estimation of q. We construct an ATS policy which uses dynamic estimators for q for control decisions and show that the associated cost coincides with that for the unknown Markov control q.

The paper has two objectives. The first is to study rigorously the transient behavior of some P2P networks whenever information is replicated and disseminated according to epidemic-like dynamics. The second is to use the insight gained from the previous analysis in order to predict how efficient are measures taken against peer-to-peer (P2P) networks. We first introduce a stochastic model which extends a classical epidemic model and characterize the P2P swarm behavior in presence of free riding peers. We then study a second model in which a peer initiates a contact with another peer chosen randomly. In both cases the network is shown to exhibit a phase transition: a small change in the parameters causes a large change in the behavior of the network. We show, in particular, how the phase transition affects measures that content provider networks may take against P2P networks that distribute non-authorized music or books, and what is the efficiency of counter-measures.

The paper has two objectives. The first is to study rigorously the transient behavior of some peer-to-peer (P2P) networks whenever information is replicated and disseminated according to epidemic-like dynamics. The second is to use the insight gained from the previous analysis in order to predict how efficient are measures taken against P2P networks. We first introduce a stochastic model which extends a classical epidemic model, and characterize the P2P swarm behavior in presence of free riding peers. We then study a second model in which a peer initiates a contact with another peer chosen randomly. In both cases the network is shown to exhibit phase transitions: a small change in the parameters causes a large change in the behavior of the network. We show, in particular, how phase transitions affect measures of content providers against P2P networks that distribute non-authorized music or books, and what is the efficiency of counter-measures.

We show global uniqueness of the solution to a class of constrained variational problems, using scaling properties. This is used to establish the essential uniqueness of solutions of a large deviations problem in multiple dimensions. The result is motivated by models of buffers, and in particular the probability of, and typical path to overflow in the limit of small buffers, which we analyze.