A great deal of attention has been applied to studying new and better ways to perform learning tasks involving static finite vectors. Indeed, over the past century the fields of statistics and machine learning have amassed a vast understanding of various learning tasks like clustering, classification, and regression using simple real valued vectors. However, we do not live in a world of simple objects. From the contact lists we keep, the sound waves we hear, and the distribution of cells we have, complex objects such as sets, distributions, sequences, and functions are all around us.
Abstract: In recent times, computer vision has made great leaps towards 2D understanding of sparse visual snapshots of the world. This is insufficient for robots that need to exist and act in the 3D world around them based on a continuous stream of multi-modal inputs. In this talk, I will present some of my efforts in bridging this gap between computer vision and robotics. I will show how thinking about computer vision and robotics together, brings out limitations of current computer vision tasks and techniques, and motivates joint perception and action solutions for robotic tasks.
The value and power mediated by the global, interconnected systems of today’s
Internet attract adversaries who seek to exploit these systems for economic,
political or social gain. Yet, the underlying complexity of Internet
infrastructure, the layering of its services, and the indirect nature of its
business relationships can make it challenging to identify even the existence
of adversaries manipulating systems for their benefit.
Deadline to RSVP is Tues., Feb. 13, 2018. The event takes place Wed., Feb. 21. Any questions or RSVPs can be directed to Ginny Mueller at gamueller [at] michaelbest.com
If you are seeking a future internship or full-time opportunity and may have an interest in working in the legal industry, please consider attending Michael Best’s Open House on Wednesday, February 21 from 5:00 – 6:30pm in our Madison Office (see attached flyer).
Abstract: 3D printing technology has been widely applied to produce well-designed objects. There is a hope to make both the modeling process and printing outputs more interactive, so that designers can get in-situ tangible feedback to fabricate objects with rich functionalities. To date, however, knowledge accumulated to realize this hope remains limited. In this talk, I will present two lines of research. The first line of work aims at facilitating an interactive process of fabrication.
Programming—the means by which we tell computers what to do—has changed a lot over time. Programming today means programming alongside hundreds of fellow students, thousands of fellow professional software engineers at a particular company, or millions of fellow developers in the open-source community sharing their code online. In this talk, I will describe several interactive systems I have built that exploit the structure within large volumes of peer-produced code to help individual programmers learn how to write more correct, readable code.
The Data & Analytics team delivers strategic business solutions for clients requiring in-depth analysis of large, disparate sets of financial, operational and transactional data. Our team of experienced consultants identifies, acquires and transforms vast amounts of critical client information, then uses FTI’s business and industry expertise to analyze problems or opportunities and identify and create solutions.
Automata learning algorithms such as the L* algorithm are a family of active
learning algorithms. They are used to automatically build a model of a system, in
the form of automata or transducers, by querying the target system and then
refining the model using counterexamples. In this talk, I will discuss new
systems, based on novel and classical automata learning algorithms, for testing
a variety of security and correctness properties in a black-box manner, i.e.
given only the ability to query the target program and without access to the