activity
20202026
most citedImproved Mechanisms and Prophet Inequalities for Graphical Dependencies

1 citations · 2 across the 15 of their papers we have counts for

collaborators

18 papers

cs.GT2026

Improved Combinatorial Auctions with and without Samples

Aviad Rubinstein, Sahil Singla

We give new mechanisms for combinatorial auctions in the offline, secretary, and prophet-with-samples models. Specifically, we obtain the following guarantees for social welfare ma…

cs.DS2026

Efficient Algorithms for Online Subadditive Combinatorial Allocations

Calum MacRury, Rian Neogi, Kanstantsin Pashkovich +4

For the online combinatorial allocation problem with subadditive valuations, Correa and Cristi (STOC 2023) proved the existence of a -competitive online algorithm, improving on…

cs.DS2026

The Cube-Root Phenomenon in Online Carpooling

Nikhil Bansal, Milind Prabhu, Sahil Singla +1

We consider the online carpooling problem, where edges arrive online and must be oriented immediately while keeping the discrepancy between the indegree and outdegree at each verte…

cs.DS2026

Online Allocation using Few Samples

Matthew Faw, Sahil Singla, Yifan Wang

We study online allocation problems where requests over resources arrive in an adversarial order and must be served immediately and irrevocably. This framework captures bot…

cs.LG2026

Adversarial Online Classification with a Preview

Roi Livni, Sahil Singla

Worst-case online classification is governed by sequential complexity, such as Littlestone dimension, and can be impossible even for statistically simple classes, such as threshold…

cs.LG2026

Online Algorithms via Minimax and Posterior Matching

Thomas Kesselheim, Marco Molinaro, Kalen Patton +1

Competitive analysis is central to the study of online algorithms, but upper bounds are often highly problem-specific. We develop a more unifying methodology via the minimax viewpo…

cs.DS2026

Philosopher and Prophet Inequalities for Divisible Items

Thiago Oliveira, Mohit Singh, Sahil Singla

We study online welfare maximization with divisible resources. A sequence of players arrive one by one; upon arrival, each player draws a valuation function over divisible…

cs.DS2026

Online Graph Balancing and the Power of Two Choices

Nikhil Bansal, Milind Prabhu, Sahil Singla +1

In the classic online graph balancing problem, edges arrive sequentially and must be oriented immediately upon arrival, to minimize the maximum in-degree. For adversarial arrivals,…

cs.DS2026

Secretary, Prophet, and Stochastic Probing via Big-Decisions-First

Aviad Rubinstein, Sahil Singla

We revisit three fundamental problems in algorithms under uncertainty: the Secretary Problem, Prophet Inequality, and Stochastic Probing, each subject to general downward-closed co…

cs.DS2025

Integral Online Algorithms for Set Cover and Load Balancing with Convex Objectives

Thomas Kesselheim, Marco Molinaro, Kalen Patton +1

Online Set Cover and Load Balancing are central problems in online optimization, and there is a long line of work on developing algorithms for these problems with convex objectives…

cs.LG2025

Improved and Oracle-Efficient Online -Multicalibration

Rohan Ghuge, Vidya Muthukumar, Sahil Singla

We study \emph{online multicalibration}, a framework for ensuring calibrated predictions across multiple groups in adversarial settings, across rounds. Although online calibrat…

cs.DS2025

Single-Sample and Robust Online Resource Allocation

Rohan Ghuge, Sahil Singla, Yifan Wang

Online Resource Allocation problem is a central problem in many areas of Computer Science, Operations Research, and Economics. In this problem, we sequentially receive stochast…

cs.GT2024

Online Combinatorial Allocations and Auctions with Few Samples

Paul Dütting, Thomas Kesselheim, Brendan Lucier +2

In online combinatorial allocations/auctions, n bidders sequentially arrive, each with a combinatorial valuation (such as submodular/XOS) over subsets of m indivisible items. The a…

cs.DS2024

Supermodular Approximation of Norms and Applications

Thomas Kesselheim, Marco Molinaro, Sahil Singla

Many classical problems in theoretical computer science involve norm, even if implicitly; for example, both XOS functions and downward-closed sets are equivalent to some norms. The…

cs.GT2024★ 1 cited

Improved Mechanisms and Prophet Inequalities for Graphical Dependencies

Vasilis Livanos, Kalen Patton, Sahil Singla

Over the past two decades, significant strides have been made in stochastic problems such as revenue-optimal auction design and prophet inequalities, traditionally modeled with …

cs.GT2024

Sample Complexity of Posted Pricing for a Single Item

Billy Jin, Thomas Kesselheim, Will Ma +1

Selling a single item to self-interested buyers is a fundamental problem in economics, where the two objectives typically considered are welfare maximization and revenue maximi…

cs.CV2024★ 1 cited

Robust Disaster Assessment from Aerial Imagery Using Text-to-Image Synthetic Data

Tarun Kalluri, Jihyeon Lee, Kihyuk Sohn +4

We present a simple and efficient method to leverage emerging text-to-image generative models in creating large-scale synthetic supervision for the task of damage assessment from a…

cs.DS2020

Efficient Approximation Schemes for Stochastic Probing and Selection-Stopping Problems

Danny Segev, Sahil Singla

In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Gi…