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

Michael Noukhovitch mnoukhov at gmail.com
Mar 17 Avr 13:58:03 EDT 2018


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Cheers,
Michael

On Mon, Apr 16, 2018 at 6:28 PM Michael Noukhovitch <mnoukhov at gmail.com>
wrote:

> 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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