[Colloquium] 2/28 Young Researcher Seminar Series: Chelsea Finn, UC Berkeley

[Mary Marre via Colloquium]

 When:     Wednesday, February 28th at *10:30 am*

Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526

Who:       Chelsea Finn, UC Berkeley


Title: Generalization and Self-Supervision in Deep Robotic Learning

Abstract: Machine learning algorithms excel primarily in settings where an
engineer can first reduce the problem to a particular function (e.g. an
image classifier), and then collect a substantial amount of labeled
input-output pairs for that function. In drastic contrast, humans are
capable of learning from streams of raw sensory data with minimal external
instruction. In this talk, I will argue that, in order to build intelligent
systems that are as capable as humans, machine learning models should not
be trained in the context of one particular application. Instead, we should
be designing systems that can be versatile, can learn in unstructured
settings without detailed human-provided labels, and can accomplish many
tasks, all while processing high-dimensional sensory inputs. To do so,
these systems must be able to actively explore and experiment, collecting
data themselves rather than relying on detailed human labels.

My talk will focus on two key aspects of this goal: versatility and
self-supervision. I will first show how we can move away from
hand-designed, task-specific representations of a robot’s environment by
enabling the robot to learn high-capacity models, such as deep networks,
for representing complex skills from raw pixels. I will also present an
algorithm that learns deep models that can be rapidly adapted to different
objects, new visual concepts, or varying environments, leading to versatile
behaviors. Beyond versatility, a hallmark of human intelligence is
self-supervised learning. I will discuss how we can allow a robot to learn
by playing with objects in the environment without any human supervision.
>From this experience, the robot can acquire a visual predictive model of
the physical world that can be used for maneuvering many different objects
to varying goals. In all settings, our experiments on simulated and real
robot platforms demonstrate the ability to scale to complex, vision-based
skills with novel objects.


Host: Matthew Walter <mwalter at ttic.edu>

************************************************************
**************************************



The TTIC Young Researcher Seminar Series (http://www.ttic.edu/young-
researcher.php) features talks by Ph.D. students and postdocs whose research is
of broad interest to the computer science community. The series provides an
opportunity for early-career researchers to present recent work to and meet
with students and faculty at TTIC and nearby universities.


The seminars are typically held on Wednesdays at 11:00am in TTIC Room 526.

For additional information, please contact Matthew Walter (mwalter at ttic.edu
).








Mary C. Marre
Administrative Assistant
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 504*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20180221/434682c9/attachment.html>