Dear all,
Next week, we have the pleasure of hosting Prof. Yonina Eldar (Weizmann
Institute of Science) at our CS colloquium. The title and abstract of the
talk, as well as a short bio of the speaker appear below.
The seminar will be held on Monday, November 18th at 14:00 (refreshments at
13:45).
*Location*: Romm C220, Rothberg Building.
Looking forward to seeing you,
Amir and Moshe
===============================
*Speaker: *Prof. Yonina Eldar
<https://www.weizmann.ac.il/math/yonina/> (Weizmann
Institute of Science)
*Title*: Model Based Deep Learning: Applications to Imaging and
Communication
*Abstract*: Deep neural networks provide unprecedented performance gains in
many real-world problems in signal and image processing. Despite these
gains, the future development and practical deployment of deep networks are
hindered by their black-box nature, i.e., a lack of interpretability and
the need for very large training sets.
On the other hand, signal processing and communications have traditionally
relied on classical statistical modeling techniques that utilize
mathematical formulations representing the underlying physics, prior
information and additional domain knowledge. Simple classical models are
useful but sensitive to inaccuracies and may lead to poor performance when
real systems display complex or dynamic behaviour. Here we introduce
various approaches to model based learning which merge parametric models
with optimization tools and classical algorithms leading to efficient,
interpretable networks from reasonably sized training sets. We will
consider examples of such model-based deep networks to image deblurring,
image separation, super resolution in ultrasound and microscopy, radar for
clinical applications, efficient communication systems, and more.
*Bio: *Yonina Eldar is a Professor in the Department of Mathematics and
Computer Science, Weizmann Institute of Science, Rehovot, Israel where she
heads the center for Biomedical Engineering and Signal Processing and holds
the Dorothy and Patrick Gorman Professorial Chair. She is also a Visiting
Professor at MIT, a Visiting Scientist at the Broad Institute, and an
Adjunct Professor at Duke University and was a Visiting Professor at
Stanford. She is a member of the Israel Academy of Sciences and
Humanities, an IEEE Fellow and a EURASIP Fellow. She received the B.Sc.
degree in physics and the B.Sc. degree in electrical engineering from
Tel-Aviv University, and the Ph.D. degree in electrical engineering and
computer science from MIT, in 2002. She has received many awards for
excellence in research and teaching, including the IEEE Signal Processing
Society Technical Achievement Award (2013), the IEEE/AESS Fred Nathanson
Memorial Radar Award (2014) and the IEEE Kiyo Tomiyasu Award (2016). She
was a Horev Fellow of the Leaders in Science and Technology program at the
Technion and an Alon Fellow. She received the Michael Bruno Memorial Award
from the Rothschild Foundation, the Weizmann Prize for Exact Sciences, the
Wolf Foundation Krill Prize for Excellence in Scientific Research, the
Henry Taub Prize for Excellence in Research (twice), the Hershel Rich
Innovation Award (three times), and the Award for Women with Distinguished
Contributions. She received several best paper awards and best demo awards
together with her research students and colleagues, was selected as one of
the 50 most influential women in Israel, and was a member of the Israel
Committee for Higher Education. She is the Editor in Chief of Foundations
and Trends in Signal Processing, a member of several IEEE Technical
Committees and Award Committees, and heads the Committee for Promoting
Gender Fairness in Higher Education Institutions in Israel.
Dear all,
Next week, we have the pleasure of hosting *Prof. Elad Hazan* (Princeton
University) at our CS colloquium. The title and abstract of the talk
appear below. For bio see here <https://www.ehazan.com/bio/>.
The seminar will be held on Monday, November 11th at 14:00.
(Refreshments at 13:45)
*Location*: Romm C220, Rothberg Building.
Looking forward to seeing you,
Amir and Moshe
===============================
*Speaker: **Prof. Elad Hazan <https://www.ehazan.com/bio/>* (Princeton
University)
*Title*: Spectral Transformers
*Abstract*: We'll discuss a new technique for sequence modeling for
prediction tasks with long range dependencies and fast
inference/generation. At the heart of the method is a new formulation for
state space models (SSMs) based on learning linear dynamical systems with
the spectral filtering algorithm.
This gives rise to a novel sequence prediction architecture we call a
spectral state space model.
Spectral state space models have two primary advantages. First, they have
provable robustness properties as their performance depends on neither the
spectrum of the underlying dynamics nor the dimensionality of the problem.
Second, these models are constructed with fixed convolutional filters that
do not require learning while still outperforming SSMs in both theory and
practice. The resulting models are evaluated on synthetic dynamical systems
as well as long-range prediction tasks of various modalities. These
evaluations support the theoretical benefits of spectral filtering for
tasks requiring very long range memory.
The talk will be self-contained, but here is a link to more information
about spectral transformers and filtering
<https://sites.google.com/view/gbrainprinceton/projects/spectral-transformers>.
Dear all,
Next week, we have the pleasure of hosting *Prof. Avi Wigderson* (IAS), the
recipient of the 2023 ACM A.M. Turing Award
<https://awards.acm.org/award-recipients/wigderson_3844537>, at our CS
colloquium.
The seminar will be held on Monday, November 4th at 14:00.
(Refreshments at 13:45)
*Location*: Auditorium, Rothberg Building (Note the unusual location)
The title and abstract appear below (and a short bio is attached).
Looking forward to seeing you,
Amir and Moshe
===============================
*Title*: Reading Alan Turing
*Abstract*:
I will discuss some well-known and less-known papers of Turing, demonstrate
the scope of deep, prescient ideas he put forth, and mention follow-up
bodies of work on these ideas by the Theoretical CS community.
[image: Avi Wigderson.png]