Anupam Gupta
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View article: Multi-Platform Autobidding with and without Predictions
Multi-Platform Autobidding with and without Predictions Open
We study the problem of finding the optimal bidding strategy for an advertiser in a multi-platform auction setting. The competition on a platform is captured by a value and a cost function, mapping bidding strategies to value and cost resp…
View article: Dynamic Analysis of a Closed Economy Using the IS-LM Model in Discrete Time
Dynamic Analysis of a Closed Economy Using the IS-LM Model in Discrete Time Open
This study introduces an economic model with an exogenous tax rate to analyze changes in income and interest rates, employing the ISLM (Investment-Saving and Liquidity reference-Money Supply) framework in macroeconomics. The deterministic …
View article: Effect of the background flow on the motility induced phase separation
Effect of the background flow on the motility induced phase separation Open
We simulate active Brownian particles (ABPs) with soft-repulsive interactions subjected to a four-roll-mill flow. In the absence of flow, this system exhibits motility-induced phase separation (MIPS). To investigate the interplay between M…
View article: Configuration balancing for stochastic requests
Configuration balancing for stochastic requests Open
The configuration balancing problem with stochastic requests generalizes well-studied resource allocation problems such as load balancing and virtual circuit routing. There are given m resources and n requests; each request has multiple po…
View article: Structural iterative rounding for generalized k-median problems
Structural iterative rounding for generalized k-median problems Open
This paper considers approximation algorithms for generalized k -median problems. These problems can be informally described as k -median with a constant number of extra constraints, and includes k -median with outliers, and knapsack media…
View article: Pairwise-Independent Contention Resolution
Pairwise-Independent Contention Resolution Open
We study online contention resolution schemes (OCRSs) and prophet inequalities for non-product distributions. Specifically, when the active set is sampled according to a pairwise-independent (PI) distribution, we show a $(1-o_k(1))$-select…
View article: Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure
Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure Open
Even for simple arithmetic tasks like integer addition, it is challenging for Transformers to generalize to longer sequences than those encountered during training. To tackle this problem, we propose position coupling, a simple yet effecti…
View article: MAC Advice for Facility Location Mechanism Design
MAC Advice for Facility Location Mechanism Design Open
Algorithms with predictions have attracted much attention in the last years across various domains, including variants of facility location, as a way to surpass traditional worst-case analyses. We study the $k$-facility location mechanism …
View article: Matroid-based TSP rounding for half-integral solutions
Matroid-based TSP rounding for half-integral solutions Open
We show how to round any half-integral solution to the subtour-elimination relaxation for the TSP, while losing a less-than $$-$$ 1.5 factor. Such a rounding algorithm was recently given by Karlin, Klein, and Oveis Gharan based on samplin…
View article: Max-Cut with $ε$-Accurate Predictions
Max-Cut with $ε$-Accurate Predictions Open
We study the approximability of the MaxCut problem in the presence of predictions. Specifically, we consider two models: in the noisy predictions model, for each vertex we are given its correct label in $\{-1,+1\}$ with some unknown probab…
View article: Early Fusion of Features for Semantic Segmentation
Early Fusion of Features for Semantic Segmentation Open
This paper introduces a novel segmentation framework that integrates a classifier network with a reverse HRNet architecture for efficient image segmentation. Our approach utilizes a ResNet-50 backbone, pretrained in a semi-supervised manne…
View article: The Average-Value Allocation Problem
The Average-Value Allocation Problem Open
We initiate the study of centralized algorithms for welfare-maximizing allocation of goods to buyers subject to average-value constraints. We show that this problem is NP-hard to approximate beyond a factor of e/(e-1), and provide a 4e/(e-…
View article: FRAG at the NTCIR-17 MedNLP-SC Task
FRAG at the NTCIR-17 MedNLP-SC Task Open
International audience
View article: The Price of Explainability for Clustering
The Price of Explainability for Clustering Open
Given a set of points in d-dimensional space, an explainable clustering is one where the clusters are specified by a tree of axis-aligned threshold cuts. Dasgupta et al. (ICML 2020) posed the question of the price of explainability: the wo…
View article: Improving Length-Generalization in Transformers via Task Hinting
Improving Length-Generalization in Transformers via Task Hinting Open
It has been observed in recent years that transformers have problems with length generalization for certain types of reasoning and arithmetic tasks. In particular, the performance of a transformer model trained on tasks (say addition) up t…
View article: Maintaining Matroid Intersections Online
Maintaining Matroid Intersections Online Open
Maintaining a maximum bipartite matching online while minimizing recourse/augmentations is a well studied problem, motivated by content delivery, job scheduling, and hashing. A breakthrough result of Bernstein, Holm, and Rotenberg (\emph{S…
View article: Efficient Algorithms and Hardness Results for the Weighted $k$-Server Problem
Efficient Algorithms and Hardness Results for the Weighted $k$-Server Problem Open
In this paper, we study the weighted $k$-server problem on the uniform metric in both the offline and online settings. We start with the offline setting. In contrast to the (unweighted) $k$-server problem which has a polynomial-time soluti…
View article: The Price of Explainability for Clustering
The Price of Explainability for Clustering Open
Given a set of points in $d$-dimensional space, an explainable clustering is one where the clusters are specified by a tree of axis-aligned threshold cuts. Dasgupta et al. (ICML 2020) posed the question of the price of explainability: the …
View article: Set Covering with Our Eyes Wide Shut
Set Covering with Our Eyes Wide Shut Open
In the stochastic set cover problem (Grandoni et al., FOCS '08), we are given a collection $\mathcal{S}$ of $m$ sets over a universe $\mathcal{U}$ of size $N$, and a distribution $D$ over elements of $\mathcal{U}$. The algorithm draws $n$ …
View article: PREDICT SURVIVAL PROBABILITY FOR CANCER PATIENTSUSING DEEP LEARNING
PREDICT SURVIVAL PROBABILITY FOR CANCER PATIENTSUSING DEEP LEARNING Open
Deep learning is a type of machine learning that uses artificial neural networks to learn and make decisions based on data. It has been applied in various fields, including healthcare, to predict the survival probabilityof cancer patients.…
View article: Nontraumatic Bilateral Neck of Femur Fracture in Elderly Male Post-seizure Attack
Nontraumatic Bilateral Neck of Femur Fracture in Elderly Male Post-seizure Attack Open
Among the femoral neck fractures, unilateral injury is the most common presenting feature.1 In the younger population, it is a result of high energy trauma from road traffic accidents or falls from height.1,2 In the elderly population, a s…
View article: Rehabilitation in Ataxia
Rehabilitation in Ataxia Open
Ataxic disorders are numerous and relatively uncommon. They can result in lesions in the cerebellum, spinal cord, thalamic nuclei, vestibular nuclei, cerebral white matter and sensory pathways. Ataxia can be acute, subacute or chronic onse…
View article: Graph Searching with Predictions
Graph Searching with Predictions Open
Consider an agent exploring an unknown graph in search of some goal state. As it walks around the graph, it learns the nodes and their neighbors. The agent only knows where the goal state is when it reaches it. How do we reach this goal wh…
View article: A Local Search-Based Approach for Set Covering
A Local Search-Based Approach for Set Covering Open
In the Set Cover problem, we are given a set system with each set having a weight, and we want to find a collection of sets that cover the universe, whilst having low total weight. There are several approaches known (based on greedy approa…
View article: Multiset multicover methods for discriminative marker selection
Multiset multicover methods for discriminative marker selection Open
Markers are increasingly being used for several high-throughput data analysis and experimental design tasks. Examples include the use of markers for assigning cell types in scRNA-seq studies, for deconvolving bulk gene expression data, and…
View article: The Power of Adaptivity for Stochastic Submodular Cover
The Power of Adaptivity for Stochastic Submodular Cover Open
Adaptivity in Stochastic Submodular Cover Solutions to stochastic optimization problems are typically sequential decision processes that make decisions one by one, waiting for (and using) the feedback from each decision. Whereas such “adap…
View article: Rehabilitation Outcome in a Case of Neurobrucellosis: Experience from a Tertiary Care Hospital in South India
Rehabilitation Outcome in a Case of Neurobrucellosis: Experience from a Tertiary Care Hospital in South India Open
We describe the clinical presentation, hospital course and rehabilitation outcome (with improvement in clinical scores) in a middle-aged male with neurobrucellosis admitted in Neurological Rehabilitation ward of a tertiary care hospital in…