7:00 – 3:30 ASRC MKT
- Call ACK today about landing pad 7s. Nope – closed today
- The Thirteenth International Conference on Spatial Information Theory (COSIT 2017)
- Topic-Relevance Map: Visualization for Improving Search Result Comprehension
- We introduce topic-relevance map, an interactive search result visualization that assists rapid information comprehension across a large ranked set of results. The topic-relevance map visualizes a topical overview of the search result space as keywords with respect to two essential information retrieval measures: relevance and topical similarity. Non-linear dimensionality reduction is used to embed high-dimensional keyword representations of search result data into angles on a radial layout. Relevance of keywords is estimated by a ranking method and visualized as radiuses on the radial layout. As a result, similar keywords are modeled by nearby points, dissimilar keywords are modeled by distant points, more relevant keywords are closer to the center of the radial display, and less relevant keywords are distant from the center of the radial display. We evaluated the effect of the topic-relevance map in a search result comprehension task where 24 participants were summarizing search results and produced a conceptualization of the result space. The results show that topic-relevance map significantly improves participants’ comprehension capability compared to a conventional ranked list presentation.
- Important to remember for the Research Browser: Where to Add Actions in Human-in-the-Loop Reinforcement Learning
- In order for reinforcement learning systems to learn quickly in vast action spaces such as the space of all possible pieces of text or the space of all images, leveraging human intuition and creativity is key. However, a human-designed action space is likely to be initially imperfect and limited; furthermore, humans may improve at creating useful actions with practice or new information. Therefore, we propose a framework in which a human adds actions to a reinforcement learning system over time to boost performance. In this setting, however, it is key that we use human effort as efficiently as possible, and one significant danger is that humans waste effort adding actions at places (states) that aren’t very important. Therefore, we propose Expected Local Improvement (ELI), an automated method which selects states at which to query humans for a new action. We evaluate ELI on a variety of simulated domains adapted from the literature, including domains with over a million actions and domains where the simulated experts change over time. We find ELI demonstrates excellent empirical performance, even in settings where the synthetic “experts” are quite poor.
- This is interesting. DARPA had a Memex project that they open-sourced
- Got PHP and xdebug set up on my home machines, mostly following these instructions. The dll that matches the PHP install needs to be downloaded from here and placed in the /php directory. Then add the following to the php.ini file:
[XDebug] zend_extension = "C:\xampp\php\ext\php_xdebug.dll" xdebug.profiler_append = 0 xdebug.profiler_enable = 1 xdebug.profiler_enable_trigger = 1 xdebug.profiler_output_dir = "C:\xampp\tmp" xdebug.profiler_output_name = "cachegrind.out.%t-%s" xdebug.remote_enable = 0 xdebug.remote_handler = "dbgp" xdebug.remote_host = "127.0.0.1" xdebug.remote_port = "9876" xdebug.trace_output_dir = "C:\xampp\tmp"
Then go to settings->Languages & Frameworks -> PHP, and either attach to the php CLI or refresh. The debugger should become visible:
- Reworking the CHI DC to a CHIIR DC
- There is a new version of the LaTex templates as of Oct 2 here. I wonder if that fixes the CHI problems?
- Put things in the right format, got the pix in the columns. Four pages! Working on fixing text.
- Finished first pass (time for multiple passes! Woohoo!)
- Working on paragraph
- Start schema for PolarizationGame
- Theresa asked me to set up a new set of CSEs. Will need a credit card and the repository location. Waiting for that.