activity
20172021
most citedFew-Shot Adversarial Domain Adaptation

207 citations · 209 across the 4 of their papers we have counts for

collaborators

5 papers

math.OC2021

The Contextual Appointment Scheduling Problem

Nima Salehi Sadghiani, Saeid Motiian

This study is concerned with the determination of optimal appointment times for a sequence of jobs with uncertain duration. We investigate the data-driven Appointment Scheduling Pr…

cs.CV2021

ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity

Dan Ruta, Saeid Motiian, Baldo Faieta +5

We present ALADIN (All Layer AdaIN); a novel architecture for searching images based on the similarity of their artistic style. Representation learning is critical to visual search…

cs.CV20192 cited

Multitask Text-to-Visual Embedding with Titles and Clickthrough Data

Pranav Aggarwal, Zhe Lin, Baldo Faieta +1

Text-visual (or called semantic-visual) embedding is a central problem in vision-language research. It typically involves mapping of an image and a text description to a common fea…

cs.CV2017207 cited

Few-Shot Adversarial Domain Adaptation

Saeid Motiian, Quinn Jones, Seyed Mehdi Iranmanesh +1

This work provides a framework for addressing the problem of supervised domain adaptation with deep models. The main idea is to exploit adversarial learning to learn an embedded su…

cs.CV2017

Unified Deep Supervised Domain Adaptation and Generalization

Saeid Motiian, Marco Piccirilli, Donald A. Adjeroh +1

This work provides a unified framework for addressing the problem of visual supervised domain adaptation and generalization with deep models. The main idea is to exploit the Siames…