Congestion control with explicit router feedback, such as TCP Quick-Start and XCP, is a promising way to enhance the performance of data transport especially in high-speed networks. When designing such transport protocols, the tradeoff between the granularity of feedback information and additional cost of routers for feedback processing and state keeping should be discussed. However, the feasib...

Abstract The recommender system (RS) has played an increasingly important role in Internet applications. Recent literature on RS mainly focused better fitting the user behavior data. However, data is observational, not experimental. This makes for a wide range of biases In this paper, we introduce novel framework to combine advantages both multi-task and curriculum learning debiased recommendat...

Background: Clinical education is the basis for medical sciences education, and one of the most critical criteria of professional education, playing a significant role in internalizing the teachings to students. This study aims to investigate the opinions of midwifery students about the quality of feedback provision in clinical education.<br /...

One of the main bottle-necks in providing more effective information access is the poverty of the query end. With an average query length of about two terms, users provide only a highly ambiguous statement of the, often complex, underlying information need. Implicit and explicit feedback can provide us with additional information that can help disambiguate the query and provide more focused sea...

Model predictive control (MPC) is a favored method for handling constrained linear control problems. Normally, the MPC optimization problem is solved on-line, but in ‘explicit MPC’ an explicit precomputed feedback law is used for each region of active constraints (Bemporad et al., 2002). In this paper we make a link between this and the ‘self-optimizing control’ idea of finding simple policies ...

Recommender systems typically require feedback from the user to learn the user’s taste. This feedback can come in two forms: explicit and implicit. Explicit feedback consists of ratings provided by the user for a number of items, while implicit feedback comes from observing user actions on items. These actions have to be interpreted by the recommender system and translated into a rating. In thi...

Acquiring novel speech categories is necessary in spoken language learning. The dual-learning systems (DLS) approach posits that two competitive systems underlie the category learning process: an explicit hypothesis-testing system, and an implicit procedural system. DLS assumes that the explicit system dominates early and control is passed to the implicit system when optimal. Evidence from our ...

Can implicit feedback substitute for explicit ratings in recommender systems? If so, we could avoid the difficulties associated with gathering explicit ratings from users. How, then, can we capture useful information unobtrusively, and how might we use that information to make recommendations? In this paper we identify three types of implicit feedback and suggest two strategies for using implic...

One common dichotomy faced in recommender systems is that explicit user feedback -in the form of ratings, tags, or user-provided personal informationis scarce, yet the most popular source of information in most state-of-the-art recommendation algorithms, and on the other side, implicit user feedback such as numbers of clicks, playcounts, or web pages visited in a sessionis more frequently avail...