## Speaker:

## Organisers:

## Time:

In this talk, we will consider algorithmic problems which follow the following template: given a real-valued multivariate polynomial f(x) of degree d, is it approximately equal to a sum of a few "simple" polynomials, i

Neeraj Kayal

Tuesday, 26 January 2021, 16:00 to 17:00

In this talk, we will consider algorithmic problems which follow the following template: given a real-valued multivariate polynomial f(x) of degree d, is it approximately equal to a sum of a few "simple" polynomials, i

Speaker:

Varun Narayanan, TIFR

Monday, 18 January 2021, 11:00 to 12:00

Information theoretically secure multiparty computation (MPC) is a central primitive in modern cryptography.

Kshitij Gajjar

Friday, 15 January 2021, 17:15 to 18:15

Many graph problems that are NP-hard for general graphs can be solved in polynomial time for planar graphs. We explore the domain of "almost" planar graphs. These are graphs that can be made planar by removing one or two vertices from them.

William K. Moses Jr.

Saturday, 9 January 2021, 10:00 to 11:00

This paper concerns designing distributed algorithms that are singularly optimal, i.e., algorithms that are simultaneously time and message optimal, for the fundamental leader election problem in networks.

Speaker:

Anamay Tengse, TIFR

Friday, 1 January 2021, 17:15 to 18:15

In the late 1990s, a paper by Razborov and Rudich pointed out a barrier towards proving boolean circuit lower bounds.

Speaker:

Anand Deo, TIFR

Friday, 18 December 2020, 17:15 to 18:15

Motivated by the increasing adoption of models which facilitate greater automation in risk management and decision-making, this talk presents a novel Importance Sampling (IS) scheme for estimating distribution tails for a rich class of objectives

Speaker:

Abhishek Singh, TIFR

Monday, 14 December 2020, 10:30 to 11:30

Mathematical proofs when written in conventional ways often contain imprecise definitions, unstated background assumptions, and inferential gaps in reasoning.

Speaker:

Anirban Bhattacharjee, TIFR

Friday, 11 December 2020, 17:15 to 18:15

In Reinforcement Learning, one often needs to evaluate a given policy using rewards observed by following another policy. This is called off-policy evaluation in Learning Theory parlance.

Jatin Batra

Thursday, 10 December 2020, 16:00 to 17:00

Scheduling provides an interesting context for optimization methods.

Prof. Dakshita Khurana

Tuesday, 8 December 2020, 17:30 to 18:30

We construct a succinct non-interactive publicly-verifiable delegation scheme for any logspace uniform circuit under the sub-exponential Learning With Errors (LWE) assumption.

Rahul Vaze's paper

Deepesh Data, graduate student in STCS, wins the 2014 Microsoft Research India PhD Fellowship.

"Maximizing Utility Among Selfish Users in Social Groups"

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