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ORCIDBelhassen Bayar
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2020 – today
- 2024
[i4]Farnoosh Javadi, Phanideep Gampa, Alyssa Woo, Xingxing Geng, Hang Zhang, Jose Sepulveda, Belhassen Bayar, Fei Wang:
LLM-based Weak Supervision Framework for Query Intent Classification in Video Search. CoRR abs/2409.08931 (2024)- 2023
- [i3]Belhassen Bayar, Phanideep Gampa, Ainur Yessenalina, Zhen Wen:
Design Principles of Robust Multi-Armed Bandit Framework in Video Recommendations. CoRR abs/2310.01419 (2023) - [i2]Phanideep Gampa, Farnoosh Javadi, Belhassen Bayar, Ainur Yessenalina:
Multi-Task Learning For Reduced Popularity Bias In Multi-Territory Video Recommendations. CoRR abs/2310.03148 (2023) - 2021
- [c13]Happy Mittal, Aniket Chakrabarti, Belhassen Bayar, Animesh Anant Sharma, Nikhil Rasiwasia:
Distantly Supervised Transformers For E-Commerce Product QA. NAACL-HLT 2021: 4008-4017 - [i1]Happy Mittal, Aniket Chakrabarti, Belhassen Bayar, Animesh Anant Sharma, Nikhil Rasiwasia:
Distantly Supervised Transformers For E-Commerce Product QA. CoRR abs/2104.02947 (2021)
2010 – 2019
- 2019
- [c12]Brian C. Hosler, Owen Mayer, Belhassen Bayar, Xinwei Zhao, Chen Chen, James A. Shackleford, Matthew Christopher Stamm:
A Video Camera Model Identification System Using Deep Learning and Fusion. ICASSP 2019: 8271-8275 - 2018
- [j3]Belhassen Bayar
, Matthew C. Stamm:
Constrained Convolutional Neural Networks: A New Approach Towards General Purpose Image Manipulation Detection. IEEE Trans. Inf. Forensics Secur. 13(11): 2691-2706 (2018) - [c11]Belhassen Bayar, Matthew C. Stamm:
Towards Open Set Camera Model Identification Using a Deep Learning Framework. ICASSP 2018: 2007-2011 - [c10]Owen Mayer, Belhassen Bayar, Matthew C. Stamm:
Learning Unified Deep-Features for Multiple Forensic Tasks. IH&MMSec 2018: 79-84 - [c9]Belhassen Bayar, Matthew C. Stamm:
Towards Order of Processing Operations Detection in JPEG-compressed Images with Convolutional Neural Networks. Media Watermarking, Security, and Forensics 2018 - 2017
- [j2]Belhassen Bayar, Nidhal Bouaynaya, Roman Shterenberg:
SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation. IEEE J. Biomed. Health Informatics 21(2): 573-581 (2017) - [c8]Belhassen Bayar, Matthew C. Stamm:
On the robustness of constrained convolutional neural networks to JPEG post-compression for image resampling detection. ICASSP 2017: 2152-2156 - [c7]Belhassen Bayar, Matthew C. Stamm:
Augmented convolutional feature maps for robust CNN-based camera model identification. ICIP 2017: 4098-4102 - [c6]Belhassen Bayar, Matthew C. Stamm:
A Generic Approach Towards Image Manipulation Parameter Estimation Using Convolutional Neural Networks. IH&MMSec 2017: 147-157 - [c5]Belhassen Bayar, Matthew C. Stamm:
Design Principles of Convolutional Neural Networks for Multimedia Forensics. Media Watermarking, Security, and Forensics 2017: 77-86 - 2016
- [c4]Belhassen Bayar, Matthew C. Stamm:
A Deep Learning Approach to Universal Image Manipulation Detection Using a New Convolutional Layer. IH&MMSec 2016: 5-10 - 2014
- [j1]Belhassen Bayar, Nidhal Bouaynaya, Roman Shterenberg:
Probabilistic Non-Negative Matrix Factorization: Theory and Application to microarray Data Analysis. J. Bioinform. Comput. Biol. 12(1) (2014) - [c3]Belhassen Bayar, Nidhal Bouaynaya, Roman Shterenberg:
Kernel reconstruction: An exact greedy algorithm for compressive sensing. GlobalSIP 2014: 1390-1393 - 2013
- [c2]Belhassen Bayar, Nidhal Bouaynaya, Roman Shterenberg:
Inference of genetic regulatory networks with unknown covariance structure. GENSiPS 2013: 74-77 - 2011
- [c1]Belhassen Bayar, Nidhal Bouaynaya, Roman Shterenberg:
Clustering gene expression data using probabilistic non-negative matrix factorization. GENSiPS 2011: 143-146
Coauthor Index
aka: Matthew Christopher Stamm
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