Conventional conversational recommender systems support interaction strategies that are hard-coded into the system in advance. In this context, Reinforcement Learning techniques h...
Abstract— Today’s networked systems are extensively instrumented for collecting a wealth of monitoring data. In this paper, we propose a framework called System-wide Similarity...
Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multi-agent ...
Obtaining (tail) probabilities from a transform function is an important topic in queueing theory. To obtain these probabilities in discrete-time queueing systems, we have to inve...
Many modern systems exploit data redundancy to improve efficiency. These systems split data into chunks, generate identifiers for each of them, and compare the identifiers among ot...
Kanat Tangwongsan, Himabindu Pucha, David G. Ander...