[Lisa_seminaires] [Tea Talk] Ankit Anand (IIT Delhi) Fri Apr 20 10:30AM AA1360

Michael Noukhovitch mnoukhov at gmail.com
Lun 16 Avr 18:28:00 EDT 2018


This week we have *Ankit Anand* from *IIT Delhi* giving a talk on *Friday
April 20* at *10:30AM* in room *AA1360*.

¡ʞlɐʇ ǝɥʇ oʇ ǝɯoɔ
Michael

*TITLE* Symmetry Aware Decision Making and Inference

*KEYWORDS *AI Planning, Graphical Models, Image Segmentation/Stereovision

*ABSTRACT*
Many traditional AI algorithms fail to scale as the problem size increases
exponentially with the number of features. This work focuses on using
symmetries and abstractions to reduce computation and memory overhead in
state-of-the-art AI and ML problems. Specifically, we exploit symmetries in
sequential decision making under uncertainty (Monte Carlo Tree Search
algorithms like UCT) and probabilistic inference. Abstractions and
symmetries though well studied in the past have mostly been used as a
preprocessing step. Our work focuses to learn symmetries and abstractions
from scratch within the algorithm itself and use the learned abstractions
and symmetries for further speeding up the state-of-the-art algorithms.
Specifically,

a) We propose ASAP-UCT and OGA-UCT which uses novel notion of Abstractions
in Monte Carlo Tree Search Algorithms like UCT

b) We apply symmetry aware graphical model inference in close to
state-of-the-art Stereovision and Image Segmentation algorithms to gain
impressive speed-ups without loss in quality

c) We propose novel notion of symmetries -"Contextual Symmetries" and
"Non-Count Symmetries" and use those for faster mixing in MCMC algorithms

Moreover, our strategies are computationally efficient and provide gains up
to 25% in International Probabilistic Planning Competition(IPPC) domains
while speeding up MAP inference in Graphical Models by 10x for Stereovision
and Segmentation without much loss in quality.

*BIO*
Ankit Anand <http://www.cse.iitd.ernet.in/~ankitanand/> is a PhD Student at
Computer Science and Engineering department of IIT Delhi. He is advised by
Dr. Parag Singla <http://www.cse.iitd.ac.in/~parags/> and Dr. Mausam
<http://homes.cs.washington.edu/~mausam/>. His primary research interests
are Artificial Intelligence Planning, Reinforcement Learning and
Probabilistic Graphical Models. He has worked extensively on applications
of Image Segmentation, Stereovision and Sequential Decision Making tasks.

He is a recipient of Tata Consultancy Services Ph.D Fellowship from
2013-2016 and has published in top tier conferences like IJCAI, AAMAS,
ICAPS and AISTATS. He is also a winner of best paper award at StarAI
workshop at IJCAI'16.
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