1 citations · 1 across the 12 of their papers we have counts for
12 papers
Active Context Selection Improves Simple Regret in Contextual Bandits
Mohammad Shahverdikondori, Jalal Etesami, Negar Kiyavash
We study the contextual multi-armed bandit problem with a finite context space (a.k.a. subpopulations), where the learner recommends a best action for each context and is evaluated…
Neighborhood-Aware Graph Labeling Problem
Mohammad Shahverdikondori, Sepehr Elahi, Patrick Thiran +1
Motivated by optimization oracles in bandits with network interference, we study the Neighborhood-Aware Graph Labeling (NAGL) problem. Given a graph , a label set of siz…
LRW-Persian: Lip-reading in the Wild Dataset for Persian Language
Zahra Taghizadeh, Mohammad Shahverdikondori, Arian Noori +1
Lipreading has emerged as an increasingly important research area for developing robust speech recognition systems and assistive technologies for the hearing-impaired. However, non…
Learning Peer Influence Probabilities with Linear Contextual Bandits
Ahmed Sayeed Faruk, Mohammad Shahverdikondori, Elena Zheleva
In networked environments, it is common for users to share recommendations about content, products, services, and possible courses of action. Whether these recommendations are acce…
Graph Learning Is Suboptimal in Causal Bandits
Mohammad Shahverdikondori, Jalal Etesami, Negar Kiyavash
We study regret minimization in causal bandits under causal sufficiency where the underlying causal structure is not known to the agent. Previous work has focused on identifying th…
Best Group Identification in Multi-Objective Bandits
Mohammad Shahverdikondori, Mohammad Reza Badri, Negar Kiyavash
We introduce the Best Group Identification problem in a multi-objective multi-armed bandit setting, where an agent interacts with groups of arms with vector-valued rewards. The per…
Graph-Dependent Regret Bounds in Multi-Armed Bandits with Interference
Fateme Jamshidi, Mohammad Shahverdikondori, Negar Kiyavash
We study multi-armed bandits under network interference, where each unit's reward depends on its own treatment and those of its neighbors in a given graph. This induces an exponent…
Pure Exploration Beyond Reward Feedback: The Role of Post-Action Context
Mohammad Shahverdikondori, Amir Mohammad Abouei, Alireza Rezaeimoghadam +1
We introduce the problem of best arm identification (BAI) with post-action context, a new BAI problem in a stochastic multi-armed bandit environment and the fixed-confidence settin…
QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
Mohammad Shahverdikondori, Ehsan Mokhtarian, Negar Kiyavash
Causal discovery is essential for understanding relationships among variables of interest in many scientific domains. In this paper, we focus on permutation-based methods for learn…
Video alignment using unsupervised learning of local and global features
Niloufar Fakhfour, Mohammad ShahverdiKondori, Sajjad Hashembeiki +2
In this paper, we tackle the problem of video alignment, the process of matching the frames of a pair of videos containing similar actions. The main challenge in video alignment is…
Computing mixed Schatten norm of completely positive maps
Mohammad ShahverdiKondori, Sio On Chan
Computing norm for matrices is a classical problem in computational mathematics and power iteration is a well-known method for computing norm f…
Vehicle trajectory prediction works, but not everywhere
Mohammadhossein Bahari, Saeed Saadatnejad, Ahmad Rahimi +4
Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the industry and research communities have acknowledged the need for such a pillar by prov…