Select a calendar:
Filter March Events by Event Type:
SUNMONTUEWEDTHUFRISAT
Events for March 07, 2013
-
IMSC Retreat 2013
Thu, Mar 07, 2013
Thomas Lord Department of Computer Science
Workshops & Infosessions
We are pleased to have you for IMSC Retreat 2013. This retreat is scheduled as a whole-day event for Thursday March 7, 2013, to be held at USC, in the Davidson Conference Center.
The Keynote will be given by Hanan Samet, Professor of Computer Science at the University of Maryland, College Park. The details of his talk are below:
Keynote Talk of the IMSC 2013 Annual Retreat
(Open, no RSVP required)
NewsStand: A Map Query Interface for News
By Professor Hanan Samet
Department of Computer Science
University of Maryland
College Park, MD 20742
hjs@cs.umd.edu
www.cs.umd.edu/~hjs
Abstract:
The NewsStand system is an example application of a general framework that we are developing to enable people to search for information using a map query interface, where the information results from monitoring the output of over 8,000 RSS news sources and is available for retrieval within minutes of publication. The advantage of doing so is that a map, coupled with an ability to vary the zoom level at which it is viewed, provides an inherent granularity to the search process that facilitates an approximate search. This distinguishes it from today's prevalent keyword-based conventional search methods that provide a very limited facility for approximate searches which are realized primarily by permitting a match via use of a subset of the keywords. However, it is often the case that users do not have a firm grasp of which keyword to use, and thus would welcome the capability for the search to also take synonyms into account. In the case of queries to spatially-referenced data, the map query interface is a step in this direction as the act of pointing at a location (e.g., by the appropriate positioning of a pointing device) and making the interpretation of the precision of this positioning specification dependent on the zoom level is equivalent to permitting the use of spatial synonyms. The issues that arise in the design of such a system including the identification of words that correspond to geographic locations are discussed, and examples are provided of the utility of the approach (including an adaptation to Tweets resulting in the TwitterStand system), thereby representing a step forward in the emerging field of computational journalism.
Biography:
Hanan Samet is a Professor of Computer Science at the University of Maryland, College Park and is a member of the Institute for Computer Studies. He is also a member of the Computer Vision Laboratory at the Center for Automation Research where he leads a number of research projects on the use of hierarchical data structures for database applications involving spatial data. He has a Ph.D from Stanford University. His doctoral dissertation dealt with proving the correctness of translations of LISP programs which was the first work in translation validation. He is the author of the recent book "Foundations of Multidimensional and Metric Data Structures" published by Morgan-Kaufmann, San Francisco, CA, in 2006 (http://www.mkp.com/multidimensional), an award winner in the 2006 best book in Computer and Information Science competition of the Professional and Scholarly Publishers (PSP) Group of the American Publishers Association (AAP), and of the first two books on spatial data structures titled "Design and Analysis of Spatial Data Structures" and "Applications of Spatial Data Structures: Computer Graphics, Image Processing and GIS" published by Addison-Wesley, Reading, MA, 1990. He is the Founding Editor-In-Chief of the ACM Transactions on Spatial Algorithms and System (TSAS), the founding chair of ACM SIGSPATIAL, a recipient of the 2009 UCGIS Research Award, 2011 ACM Paris Kanellakis Theory and Practice Award, the 2010 CMPS Board of Visitors Award at the University of Maryland, a Fellow of the ACM, IEEE, AAAS, and IAPR (International Association for Pattern Recognition), and an ACM Distinguished Speaker. He received best paper awards in the 2008 SIGMOD Conference and the 2008 SIGSPATIAL ACMGIS'08 Conference, and a best demo award at the 2011 SIGSPATIAL ACMGIS'11 Conference. His paper at the 2009 IEEE International Conference on Data Engineering (ICDE) was selected as one of the best papers for publication in the IEEE Transactions on Knowledge and Data Engineering.More Information: imsc_retreat__agenda_2013_schedule_only.pdf
Location: Charlotte S. & Davre R. Davidson Continuing Education Conference Center (DCC) -
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
Bootstrapping Vehicles: a Formal Approach to Unsupervised Sensorimotor Learning Based on Invariance
Thu, Mar 07, 2013 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Andrea Censi, Caltech
Talk Title: CS Colloquium: Andrea Censi (CalTech)
Series: CS Colloquium
Abstract: Imagine you are a brain that wakes up in an unknown (robotic) body. You are connected to two streams of uninterpreted observations and commands. You have zero prior information on the body morphology, its sensors, its actuators, and the external world. Would you be able to "bootstrap" a model of your body from scratch, in an unsupervised manner, and use it to perform useful tasks? This bootstrapping problem sits at the intersection of numerous scientific questions and engineering problems. Biology gives us a proof of existence of a solution, given that the neocortex demonstrates similar abilities.
I am interested in understanding whether the bootstrapping problem can be formalized to the point where it can be solved with the rigour of control theory. I will discuss a tractable subset of the set of all robots called the "Vehicles Universe", which I consider a pimped-up version, with modern sensors, of Braitenberg's Vehicles. I will show that the dynamics of three "canonical" robotic sensors (camera, range-finder, field sampler) are very similar at the "sensel" level. I will present classes of models that can capture the dynamics of those sensors simultaneously and allow exactly the same agent to perform equivalent spatial tasks when embodied in different robots. I will discuss immediate applications to intrinsic sensor calibration and fault detection.
A key concern of mine is to precisely characterize the "assumptions" of the agents. I will show that assumptions regarding the representation of the data can be described by the largest group of transformations on observations/commands to which the agent behavior is invariant. This suggests that one of the basic concerns of a bootstrapping agent is being able to reject these "representation nuisances".
Reference: the homonymous dissertation, available at http://purl.org/censi/2012/phd
Biography: Andrea Censi is a postdoctoral scholar in Computing and Mathematical Sciences at the California Institute of Technology. He received the Laurea and Laurea Specialistica degrees (summa cum laude) in control engineering and robotics from Sapienza University of Rome, Italy, in 2005 and 2007, respectively, and a Ph.D. in Control & Dynamical Systems from the California Institute of Technology in 2012. He is broadly interested in perception and decision making problems for natural and artificial embodied agents, and in particular in estimation, filtering, and learning in robotics.
Website: http://andrea.caltech.edu/
Host: Fei Sha
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
