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Conferences, Lectures, & Seminars
Events for November
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CS Colloquium: Bert Zwart (CWI - Stochastics) - Learning and Earning
Tue, Nov 04, 2014 @ 11:00 AM - 12:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Bert Zwart , CWI - Stochastic Group
Talk Title: Learning and Earning
Series: CS Colloquium
Abstract: Price experimentation is an important tool for firms to find the optimal selling price of their products and has become more popular due to the rise of internet as a sales channel. It should be conducted properly, since experimenting with selling prices can be costly. A firm therefore needs to find a pricing policy that optimally balances between learning the optimal price and gaining revenue. The topic is exciting from an academic standpoint, bridging control, game theory, machine learning, operations research and statistics.
We investigate the so-called 'certainty equivalent pricing' policy, where estimating consumer behavior and optimizing profit are completely decoupled, and discuss situations where this rule may or may not lead to the profit rate that is achievable. It turns out that it is sometimes necessary to develop algorithms that ensure that the right amount of price experimentation is undertaken so as to learn and exploit consumer behavior as efficiently as possible.
This is based on joint work with Arnoud den Boer (UTwente, NL)
Biography: Bert Zwart is a researcher at CWI, where he leads the Stochastic group. He also holds secondary positions at VU University Amsterdam (Professor), Georgia Tech (Adjunct Professor) and the Dutch research center on Stochastics, Eurandom. Before that he was holding a Coca-Cola Chair at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. His research is in applied probability and stochastic operations research, inspired by problems in computer, communication, energy and service networks. Bert Zwart is the 2008 recipient of the Erlang prize for outstanding contributions to applied probability by a researcher not older than 35 years old, an IBM faculty award, VENI and VIDI awards from the Dutch Science Foundation NWO, numerous best papers awards, and co-authered more than 100 refereed publications. Bert has been area editor of Stochastic Models for the journal Operations Research, the flagship journal of his profession, since 2009, and serves on several additional journal boards and TPC's.
Host: Leana Golubchik
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Distinguished Lecture: Dr. Gregory D. Hager (Johns Hopkins University)
Tue, Nov 04, 2014 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Gregory D. Hager, Johns Hopkins University
Talk Title: Shaping the Future of Computing Research: Renaissance, Enlightenment, or Diaspora?
Series: CS Distinguished Lectures
Abstract: In 1822, Charles Babbage did an amazing thing - he realized that machines designed to perform physical work could process information. It would be over 100 years before electronic devices would allow effective realizations of his ideas. It would take an additional 40 years before computers became household devices, but only another 20 years until smart mobile devices revolutionized the connection between people, information, and the world around them. In those 60 years, computing has forged new industries, reshaped the workforce, invented new ways to interact and recreate, and reshaped society.
What are the implications of these trends for the computing research community? Where might new drivers for the field emerge, and where will they lead us? How can we frame future challenges and opportunities to ensure the continued health and growth of the field?
In this talk, I will offer some perspectives on computing research, how it is evolving, and some of the forces at work in shaping its future. I will relate some examples of how the Computing Community Consortium has successfully catalyzed efforts at creating new national computing initiatives and offer some perspective on new opportunities going forward.
Streaming for this talk will be available HERE at 3:30 PM.
Biography: Gregory D. Hager is Professor and Chair of Computer Science at Johns Hopkins University. He is also Chair of the Computing Community Consortium which has the mission of catalyzing the computing research community and enable the pursuit of innovative, high-impact research. He received his MSE and PhD from the University of Pennsylvania in 1986 and 1988, respectively. After a year as a Fulbright scholar at the University of Karlsruhe, he joined the faculty of Yale University in 1990. He moved to Johns Hopkins in 1999. His research interests include image-guided robotics, human-machine collaboration, and medical applications of image analysis and robotics. He has served as the Deputy Director of the NSF Engineering Research Center for Computer Integrated Surgical Systems and Technology, he serves on board of the International Federation of Robotics Research and is a fellow of the IEEE for his contributions to vision-based robotics.
Host: Wyatt Lloyd
Webcast: https://bluejeans.com/737763866Location: Henry Salvatori Computer Science Center (SAL) - 101
WebCast Link: https://bluejeans.com/737763866
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Steve Chien (JPL) - Using Constraint-based Search to Schedule Science Campaigns for the Rosetta Orbiter
Wed, Nov 05, 2014 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Steve Chien, JPL
Talk Title: Using Constraint-based Search to Schedule Science Campaigns for the Rosetta Orbiter
Series: CS Colloquium
Abstract: In August 2014, Rosetta (http://blogs.esa.int/rosetta/) entered orbit around the comet Churyumov-Gerasimenko. Rosetta, a European Space Agency led mission to explore the comet Churyumov-Gerasimenko, will be the first mission to deploy a soft lander to a comet, and to escort a comet for an extended period (over one year).
But Rosetta is also a pathfinding space mission from the perspective of Operations, Computer Science, and Artificial Intelligence in itâs usage of the ASPEN Artificial Intelligence planning and scheduling software for early to mid-range science activity scheduling. In my talk I first briefly discuss comets and their importance understanding the evolution of our solar system and life on Earth. Second, I describe elements of the multi- disciplinary Roseta science planning process which incorporates diverse science, geometric, engineering, and resource constraints. Finally, I describe the constraint-driven scheduling automation and how AI has much to offer not only in schedule generation, but in constraint enforcement, problem and constraint analysis, and in iterative schedule refinement.
Biography: Dr. Steve Chien is Head of the Artificial Intelligence Group and Senior Research Scientist at the Jet Propulsion Laboratory, California Institute of Technology where he leads efforts in autonomous systems for space exploration.
Dr. Chien was a recipient of the 1995 Lew Allen Award for Excellence, JPLs highest award recognizing outstanding technical achievements by JPL personnel in the early years of their careers. In 1997, he received the NASA Exceptional Achievement Medal for his work in research and development of planning and scheduling systems for NASA. He is the Team Lead for the ASPEN Planning System , which received Honorable Mention in the 1999 Software of the Year Competition and was a contributor to the Remote Agent System which was a co-winner in the same 1999 competition. In 2000, he received the NASA Exceptional Service Medal for service and leadership in research and deployment of planning and scheduling systems for NASA. He is the Principal Investigator for the Autonomous Sciencecraft Experiment which is a co-winner of the 2005 NASA Software of the Year Award. In 2007, he received the NASA Exceptional Achievement Medal for outstanding technical accomplishments in the development of the Autonomous Sciencecraft deployed on the Earth Observing One Mission and the development of the Earth Observing Sensorweb. He also led the deployment of the WATCH software to operational use onboard the Mars rover Opportunity to autonomously detect dust devils and cloud formations. In 2011 He was awarded the innaugural AIAA Intelligent Systems Award, for his contributions to Spacecraft Autonomy. In 2011, he was the team co-lead for the Sensorweb Toolbox team, which was awarded Honorable mention in the 2011 NASA Software of the Year Competition. He is the principal investigator of the IPEX cubesat, which launched in December 2013, which uses onboard image processing and automated planning software. He is currently leading the deployment of ASPEN for scheduling science observations for the Rosetta mission, an ESA-led mission to explore the comet Churyumov-Gerasimenko.
For additional information please visit: http://ai.jpl.nasa.gov/public/home/chien/
Host: Sven Koenig
Location: James H. Zumberge Hall Of Science (ZHS) - 352
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Student Colloquium: Boqing Gong - Kernel Methods for Domain Adaptation
Thu, Nov 06, 2014 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Boqing Gong, USC
Talk Title: Kernel Methods for Domain Adaptation
Series: Student Seminar Series
Abstract: The problem of domain adaptation occurs when the test data (of a target domain) and training data (of some source domain(s)) are generated by different distributions. It arises in a variety of applications, including computer vision, natural language process, speech recognition, etc.
In this talk, I will present some of our recent efforts on unsupervised domain adaptation using kernel methods. One cannot solve the domain adaptation problems given arbitrary source-target pairs. We have to explore the structures or properties in data, under which potentially successful solutions exist. Kernel methods are versatile in modeling such structures or properties. I will demonstrate several kernel methods ("kernel trick", discriminative multiple kernel learning, kernel embedding of distributions, etc.) which have been successfully used to model the structures of subspaces, landmarks, and latent domains. I will also present a sequential determinantal point process (seqDPP) with applications to supervised video summarization. This serves as the starting point of my future work on domain adaptation for video analysis.
Host: CS Department
More Information: GBQ.png
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Sachin Patil (UC Berkeley) -Coping with Uncertainty in Robotic Navigation, Exploration, and Grasping
Tue, Nov 11, 2014 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sachin Patil , UC Berkeley
Talk Title: Coping with Uncertainty in Robotic Navigation, Exploration, and Grasping
Series: CS Colloquium
Abstract: A key challenge in robotics is to robustly complete navigation, exploration, and manipulation tasks when the state of the world is uncertain. This is a fundamental problem in several application areas such as logistics, personal robotics, and healthcare where robots with imprecise actuation and sensing are being deployed in unstructured environments. In such a setting, it is necessary to reason about the acquisition of perceptual knowledge and to perform information gathering actions as necessary. In this talk, I will present an approach to motion planning under motion and sensing uncertainty called "belief space" planning where the objective is to trade off exploration (gathering information) and exploitation (performing actions) in the context of performing a task. In particular, I will present how we can use trajectory optimization to compute locally-optimal solutions to a determinized version of this problem in Gaussian belief spaces. I will show that it is possible to obtain significant computational speedups without explicitly optimizing over the covariances by considering a partial collocation approach. I will also address the problem of computing such trajectories, given that measurements may not be obtained during execution due to factors such as limited field of view of sensors and occlusions. I will demonstrate this approach in the context of robotic grasping in unknown environments where the robot has to simultaneously explore the environment and grasp occluded objects whose geometry and positions are initially unknown.
Biography: Sachin Patil is a postdoctoral researcher working with Prof. Pieter Abbeel and Prof. Ken Goldberg at the University of California at Berkeley. He previously completed his PhD with Prof. Ron Alterovitz at University of North Carolina at Chapel Hill. His research focuses on developing rigorous motion planning algorithms to enable new, minimally invasive medical procedures and to facilitate reliable operation of robots in unstructured environments.
Host: Gaurav Sukhatme
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Sergey Levine (UC Berkeley) - Learning to Move: Machine Learning for Robotics and Animation
Thu, Nov 13, 2014 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sergey Levine , UC Berkeley
Talk Title: Learning to Move: Machine Learning for Robotics and Animation
Series: CS Colloquium
Abstract: Being able to acquire new motion skills autonomously could help robots build rich motion repertoires suitable for tackling complex, varied environments. I will discuss my work on motion skill learning for robotics, including methods for learning from demonstration and reinforcement learning. In particular, I will describe a class of "guided" policy search algorithms, which combine reinforcement learning and learning from demonstration to acquire multiple simple, trajectory-centric policies, with a supervised learning phase to obtain a single complex, high-dimensional policy that can then generalize to new situations. I will show applications of this method to simulated bipedal locomotion, as well as a range of robotic manipulation tasks, including putting together two parts of a plastic toy and screwing bottle caps onto bottles. I will also discuss how such techniques can be applied to character animation in computer graphics, and how this field can inform research in robotics.
Biography: Sergey Levine is a postdoctoral researcher working with Professor Pieter Abbeel at the University of California at Berkeley. He previously completed his PhD with Professor Vladlen Koltun at Stanford University. His research areas include robotics, reinforcement learning and optimal control, machine learning, and computer graphics. His work includes the development of new algorithms for learning motor skills, methods for learning behaviors from human demonstration, and applications in robotics and computer graphics, ranging from robotic manipulation to animation of martial arts and conversational hand gestures.
Host: Fei Sha
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Rajiv Gandhi (Rutgers University-Camden) - From Potential to Promise - Developing Scholars, one Eureka moment at a time
Thu, Nov 20, 2014 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rajiv Gandhi , Rutgers University-Camden
Talk Title: From Potential to Promise - Developing Scholars, one Eureka moment at a time
Series: CS Colloquium
Abstract: In this talk, I will tell the story of our work with some truly remarkable undergraduate students at Rutgers-Camden, who despite many odds have achieved success that is unprecedented for the Camden campus. I will discuss the various challenges that we faced and some ideas that have worked very well (and some that have not) for us. We have been applying some of these ideas in our work with high school students and students at other institutions. Additional information can be found at the website for the Program in Theoretical CS: http://rajivgandhics.wordpress.com (website constructed and maintained by high school students)
Biography: Dr. Rajiv Gandhi is an Associate Professor of Computer Science at the Rutgers University-Camden. He received his Ph.D. in Computer Science from the University of Maryland, College Park in 2003. His research interests lie in the broad area of theoretical computer science. Specifically, he is interested in approximation and randomized algorithms, distributed algorithms, and graph theory. He has published papers in these areas in leading journals and conferences. He has been the recipient of several teaching excellence awards -- at Rutgers and at other universities. He was also the recipient of the Chancellor's award for Civic Engagement at Rutgers-Camden in 2013. He was a Fulbright Fellow from Jan-June 2011, during which he worked with students in Mumbai. Since 2009, he has also been working with high school students as part of the Program in Algorithmic and Combinatorial Thinking.
Host: Leana Golubchik
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
