14 citations · 74 across the 36 of their papers we have counts for
42 papers
BRANCH-MoE: Balance-Aware Tree Routing for Large Embedding Models
Gang Fu, Adel Javanmard, MohammadHossein Bateni +1
Mixture-of-experts (MoE) layers increase model capacity without a proportional increase in per-example computation. However, conventional flat routers can yield imbalanced expert u…
Optimal Networks for Agentic Information Aggregation
MohammadHossein Bateni, Zahra Hadizadeh, MohammadTaghi Hajiaghayi +2
We study information aggregation in the networked learning model introduced by Kearns, Roth, and Ryu (SODA 2026). There is a fixed distribution over features and a common label…
Optimal Rates for Agentic Networked Information Aggregation
MohammadHossein Bateni, Zahra Hadizadeh, MohammadTaghi Hajiaghayi +2
Building on the pioneering paper of Kearns, Roth, and Ryu (SODA'26), we study information aggregation in a networked learning model. The model captures a central pattern in agentic…
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…