11 papers
Networked Information Aggregation for Binary Classification
MohammadHossein Bateni, Zahra Hadizadeh, MohammadTaghi Hajiaghayi +2
We study networked binary classification on a directed acyclic graph (DAG) where each agent observes only a subset of the feature columns of a shared dataset. Agents act sequential…
Replicable Composition
Kiarash Banihashem, MohammadHossein Bateni, Hossein Esfandiari +2
Replicability requires that algorithmic conclusions remain consistent when rerun on independently drawn data. A central structural question is composition: given problems each…
Chamfer-Linkage for Hierarchical Agglomerative Clustering
Kishen N Gowda, Willem Fletcher, MohammadHossein Bateni +4
Hierarchical Agglomerative Clustering (HAC) is a widely-used clustering method based on repeatedly merging the closest pair of clusters, where inter-cluster distances are determine…
Budget Allocation for Unknown Value Functions in a Lipschitz Space
MohammadHossein Bateni, Hossein Esfandiari, Samira HosseinGhorban +2
Building learning models frequently requires evaluating numerous intermediate models. Examples include models considered during feature selection, model structure search, and param…
Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
Nilay Naharas, Dang Nguyen, Nesihan Bulut +3
Data-efficient learning aims to eliminate redundancy in large training datasets by training models on smaller subsets of the most informative examples. While data selection has bee…
Parallel Hierarchical Agglomerative Clustering in Low Dimensions
MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher +4
Hierarchical Agglomerative Clustering (HAC) is an extensively studied and widely used method for hierarchical clustering in based on repeatedly merging the closest p…