Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation

We propose a hierarchically structured reinforcement learning approach to address the challenges of planning for generating coherent multi-sentence stories for the visual storytelling task. Within our framework, the task of generating a story given a sequence of images is divided across a two-level hierarchical decoder. The high-level decoder constructs a plan by generating a semantic concept (i.e., topic) for each image in sequence. The low-level decoder generates a sentence for each image using a semantic compositional network, which effectively grounds the sentence generation conditioned on the topic. The two decoders are jointly trained end-to-end using reinforcement learning. We evaluate our model on the visual storytelling (VIST) dataset. Empirical results from both automatic and human evaluations demonstrate that the proposed hierarchically structured reinforced training achieves significantly better performance compared to a strong flat deep reinforcement learning baseline.Comment: Accepted to AAAI 201

Recursively invoking Linnaeus: A Taxonomy for Naming Systems

Naming is a central element of a distributed or network system design. Appropriate design choices are central. This paper explores a taxonomy of naming systems, and engineering tradeoffs as an aid to the namespace designer. The three orthogonal components of the taxonomy are the characteristics of the namespace itself, name assignment, and name resolution. Within each of these, we explore a number of distinct characteristics. The position of this paper is that engineering design of naming systems should be informed by the possibilities and tradeoffs that those possibilities represent. The paper includes a review of a sampling of naming system designs that reflect different choices within the taxonomy and discussion about why those choices were made.This effort was sponsored by the Defense Advanced Research Projects Agency (DARPA) and Air Force Research Laboratory, Air Force Materiel Command, USAF, under agreement number F30602-00-2-0553

Modeling interactive memex-like applications based on self-modifiable petri nets

This paper introduces an interactive Memex-like application using a self-modifiable Petri Net model – Self-modifiable Color Petri Net (SCPN). The Memex (“memory extender”) device proposed by Vannevar Bush in 1945 focused on the problems of “locating relevant information in the published records and recording how that information is intellectually connected.” The important features of Memex include associative indexing and retrieval. In this paper, the self-modifiable functions of SCPN are used to achieve trail recording and retrieval. A place in SCPN represents a website and an arc indicates the trail direction. Each time when a new website is visited, a place corresponding to this website will be added. After a trail is built, users can use it to retrieve the websites they have visited. Besides, useful user interactions are supported by SCPN to achieve Memex functions. The types of user interactions include: forward, backward, history, search, etc. A simulator has been built to demonstrate that the SCPN model can realize Memex functions. Petri net instances can be designed to model trail record, back, and forward operations using this simulator. Furthermore, a client-server based application system has been built. Using this system, a user can surf online and record his surfing history on the server according to different topics and share them with other users

Quakers and Creation Care: Potentials and Pitfalls for an Ecotheology of Friends (Chapter Five in Quakers, Creation Care, and Sustainability)

While Friends have a strong tradition of activism around the social justice issues of each era, we also tend to spiritualize our faith, disconnecting it from the material world. Environmental concerns are arguably one of the most important social justice issues of of our time, and in many ways, activism, advocacy, and lifestyle witness seem like natural ways for Friends to engage in social justice in this time in history. This essay will explore some of the historical and theological strengths Friends can draw from our tradition that can help build a particularly Quaker ecotheology, as well as some of the portions of the Friends tradition that get in the way of practicing our faith in a more sustainable way

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework