activity
20142020
most citedUnderstanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation

15 citations · 36 across the 12 of their papers we have counts for

collaborators

12 papers

cs.GT2020

Improved Truthful Mechanisms for Subadditive Combinatorial Auctions: Breaking the Logarithmic Barrier

Sepehr Assadi, Thomas Kesselheim, Sahil Singla

We present a computationally-efficient truthful mechanism for combinatorial auctions with subadditive bidders that achieves an -approximation to the maximum w…

cs.DS20194 cited

Robust Algorithms for the Secretary Problem

Domagoj Bradac, Anupam Gupta, Sahil Singla +1

In classical secretary problems, a sequence of elements arrive in a uniformly random order, and we want to choose a single item, or a set of size . The random order model al…

cs.DS20191 cited

Faster Matroid Intersection

Deeparnab Chakrabarty, Yin Tat Lee, Aaron Sidford +2

In this paper we consider the classic matroid intersection problem: given two matroids $\M_{1}=(V,\I_{1})$ and $\M_{2}=(V,\I_{2})$ defined over a common ground set , compute a s…

cs.GT2019

Improved Truthful Mechanisms for Combinatorial Auctions with Submodular Bidders

Sepehr Assadi, Sahil Singla

A longstanding open problem in Algorithmic Mechanism Design is to design computationally-efficient truthful mechanisms for (approximately) maximizing welfare in combinatorial aucti…

cs.DS20192 cited

Algorithms and Adaptivity Gaps for Stochastic -TSP

Haotian Jiang, Jian Li, Daogao Liu +1

Given a metric and a , the classic $\textsf{$k$-TSP}$ problem is to find a tour originating at the of minimum length that visits at lea…

cs.DS20194 cited

Online Geometric Discrepancy for Stochastic Arrivals with Applications to Envy Minimization

Haotian Jiang, Janardhan Kulkarni, Sahil Singla

Consider a unit interval in which points arrive one-by-one independently and uniformly at random. On arrival of a point, the problem is to immediately and irrevocably c…