activity
20222024
most citedAn Incremental Learning framework for Large-scale CTR Prediction

10 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Clouds

Elona Dupont, Kseniya Cherenkova, Dimitrios Mallis +3

3D reverse engineering, in which a CAD model is inferred given a 3D scan of a physical object, is a research direction that offers many promising practical applications. This paper…

cs.CV2023

Self-Supervised Learning for Visual Relationship Detection through Masked Bounding Box Reconstruction

Zacharias Anastasakis, Dimitrios Mallis, Markos Diomataris +3

We present a novel self-supervised approach for representation learning, particularly for the task of Visual Relationship Detection (VRD). Motivated by the effectiveness of Masked…

cs.CV2023

Interpretable Visual Question Answering via Reasoning Supervision

Maria Parelli, Dimitrios Mallis, Markos Diomataris +1

Transformer-based architectures have recently demonstrated remarkable performance in the Visual Question Answering (VQA) task. However, such models are likely to disregard crucial…

cs.CV20231 cited

SHARP Challenge 2023: Solving CAD History and pArameters Recovery from Point clouds and 3D scans. Overview, Datasets, Metrics, and Baselines

Dimitrios Mallis, Sk Aziz Ali, Elona Dupont +6

Recent breakthroughs in geometric Deep Learning (DL) and the availability of large Computer-Aided Design (CAD) datasets have advanced the research on learning CAD modeling processe…

cs.IR202210 cited

An Incremental Learning framework for Large-scale CTR Prediction

Petros Katsileros, Nikiforos Mandilaras, Dimitrios Mallis +3

In this work we introduce an incremental learning framework for Click-Through-Rate (CTR) prediction and demonstrate its effectiveness for Taboola's massive-scale recommendation ser…