1 citations · 1 across the 7 of their papers we have counts for
8 papers
The Existence of Maximin Share Allocations is -complete
Sushmita Gupta, Sanjay Seetharaman
The maximin share (MMS) guarantee has become one of the central fairness benchmarks for allocating indivisible items. Since Kurokawa, Procaccia and Wang~[EC'14, JACM'18] showed tha…
Robust Value Maximization in Challenge the Champ Tournaments with Probabilistic Outcomes
Umang Bhaskar, Juhi Chaudhary, Sushmita Gupta +2
Challenge the Champ is a simple tournament format, where an ordering of the players -- called a seeding -- is decided. The first player in this order is the initial champ, and face…
When agents choose bundles autonomously: guarantees beyond discrepancy
Sushmita Gupta, Pallavi Jain, Sanjay Seetharaman +1
We consider the fair division of indivisible items among agents with additive non-negative normalized valuations, with the goal of obtaining high value guarantees, that is, clo…
A Simple Algorithm for Combinatorial n-Fold ILPs Using the Steinitz Lemma
Sushmita Gupta, Pallavi Jain, Sanjay Seetharaman +1
We present an algorithm for a class of -fold ILPs whose existing algorithms in literature are often either (1) based on the \textit{augmentation framework} where one starts with…
Quick-Sort Style Approximation Algorithms for Generalizations of Feedback Vertex Set in Tournaments
Sushmita Gupta, Sounak Modak, Saket Saurabh +1
A feedback vertex set (FVS) in a digraph is a subset of vertices whose removal makes the digraph acyclic. In other words, it hits all cycles in the digraph. Lokshtanov et al. [TALG…
More Effort Towards Multiagent Knapsack
Sushmita Gupta, Pallavi Jain, Sanjay Seetharaman
In this paper, we study some multiagent variants of the knapsack problem. Fluschnik et al. [AAAI 2019] considered the model in which every agent assigns some utility to every item.…
Gradient-based Data Subversion Attack Against Binary Classifiers
Rosni K Vasu, Sanjay Seetharaman, Shubham Malaviya +2
Machine learning based data-driven technologies have shown impressive performances in a variety of application domains. Most enterprises use data from multiple sources to provide q…
Influence Based Defense Against Data Poisoning Attacks in Online Learning
Sanjay Seetharaman, Shubham Malaviya, Rosni KV +2
Data poisoning is a type of adversarial attack on training data where an attacker manipulates a fraction of data to degrade the performance of machine learning model. Therefore, ap…