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Amir Saffari
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2020 – today
- 2023
- [c29]Peerat Limkonchotiwat, Weiwei Cheng, Christos Christodoulopoulos, Amir Saffari, Jens Lehmann:
mReFinED: An Efficient End-to-End Multilingual Entity Linking System. EMNLP (Findings) 2023: 15080-15089 - [i10]Jinheon Baek, Alham Fikri Aji, Amir Saffari:
Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering. CoRR abs/2306.04136 (2023) - 2022
- [c28]Priyanka Sen, Alham Fikri Aji, Amir Saffari:
Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering. COLING 2022: 1604-1619 - [c27]Andy Rosenbaum, Saleh Soltan, Wael Hamza, Marco Damonte, Isabel Groves, Amir Saffari:
CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing. AACL/IJCNLP (2) 2022: 444-462 - [i9]Priyanka Sen, Alham Fikri Aji, Amir Saffari:
Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering. CoRR abs/2210.01613 (2022) - [i8]Andy Rosenbaum, Saleh Soltan, Wael Hamza, Amir Saffari, Marco Damonte, Isabel Groves:
CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing. CoRR abs/2210.07074 (2022) - 2021
- [c26]Amir Saffari, Armin Oliya, Priyanka Sen, Tom Ayoola:
End-to-End Entity Resolution and Question Answering Using Differentiable Knowledge Graphs. EMNLP (1) 2021: 4193-4200 - [c25]Priyanka Sen, Armin Oliya, Amir Saffari:
Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection. EMNLP (1) 2021: 8805-8812 - [i7]Gaurav Singh, Siffi Singh, Joshua Wong, Amir Saffari:
Relation Extraction from Tables using Artificially Generated Metadata. CoRR abs/2108.10750 (2021) - [i6]Priyanka Sen, Amir Saffari, Armin Oliya:
Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection. CoRR abs/2109.05808 (2021) - [i5]Armin Oliya, Amir Saffari, Priyanka Sen, Tom Ayoola:
End-to-End Entity Resolution and Question Answering Using Differentiable Knowledge Graphs. CoRR abs/2109.05817 (2021) - 2020
- [c24]Hamza Harkous, Isabel Groves, Amir Saffari:
Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity. COLING 2020: 2410-2424 - [c23]Priyanka Sen, Amir Saffari:
What do Models Learn from Question Answering Datasets? EMNLP (1) 2020: 2429-2438 - [i4]Priyanka Sen, Amir Saffari:
What do Models Learn from Question Answering Datasets? CoRR abs/2004.03490 (2020) - [i3]Hamza Harkous, Isabel Groves, Amir Saffari:
Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity. CoRR abs/2004.06577 (2020)
2010 – 2019
- 2018
- [i2]Rim Assouel, Mohamed Ahmed, Marwin H. S. Segler, Amir Saffari, Yoshua Bengio:
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation. CoRR abs/1811.09766 (2018) - [i1]Daniel Neil, Joss Briody, Alix Lacoste, Aaron Sim, Páidí Creed, Amir Saffari:
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs. CoRR abs/1812.00279 (2018) - 2016
- [j4]Sam Hare, Stuart Golodetz, Amir Saffari, Vibhav Vineet, Ming-Ming Cheng, Stephen L. Hicks, Philip H. S. Torr:
Struck: Structured Output Tracking with Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 38(10): 2096-2109 (2016) - 2014
- [c22]Matej Kristan, Roman P. Pflugfelder, Ales Leonardis, Jiri Matas, Luka Cehovin, Georg Nebehay, Tomás Vojír, Gustavo Fernández, Alan Lukezic, Aleksandar Dimitriev, Alfredo Petrosino, Amir Saffari, Bo Li, Bohyung Han, Cherkeng Heng, Christophe Garcia, Dominik Pangersic, Gustav Häger, Fahad Shahbaz Khan, Franci Oven, Horst Possegger, Horst Bischof, Hyeonseob Nam, Jianke Zhu, Jijia Li, Jin Young Choi, Jinwoo Choi, João F. Henriques, Joost van de Weijer, Jorge Batista, Karel Lebeda, Kristoffer Öfjäll, Kwang Moo Yi, Lei Qin, Longyin Wen, Mario Edoardo Maresca, Martin Danelljan, Michael Felsberg, Ming-Ming Cheng, Philip H. S. Torr, Qingming Huang, Richard Bowden, Sam Hare, Samantha YueYing Lim, Seunghoon Hong, Shengcai Liao, Simon Hadfield, Stan Z. Li, Stefan Duffner, Stuart Golodetz, Thomas Mauthner, Vibhav Vineet, Weiyao Lin, Yang Li, Yuankai Qi, Zhen Lei, Zhi Heng Niu:
The Visual Object Tracking VOT2014 Challenge Results. ECCV Workshops (2) 2014: 191-217 - 2013
- [c21]Samuel Schulter, Paul Wohlhart, Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof:
Alternating Decision Forests. CVPR 2013: 508-515 - 2012
- [c20]Sam Hare, Amir Saffari, Philip H. S. Torr:
Efficient online structured output learning for keypoint-based object tracking. CVPR 2012: 1894-1901 - 2011
- [c19]Christian Leistner, Martin Godec, Samuel Schulter, Amir Saffari, Manuel Werlberger, Horst Bischof:
Improving classifiers with unlabeled weakly-related videos. CVPR 2011: 2753-2760 - [c18]Sam Hare, Amir Saffari, Philip H. S. Torr:
Struck: Structured output tracking with kernels. ICCV 2011: 263-270 - [c17]Ziming Zhang, Lubor Ladicky, Philip H. S. Torr, Amir Saffari:
Learning Anchor Planes for Classification. NIPS 2011: 1611-1619 - 2010
- [j3]Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley:
Model Selection: Beyond the Bayesian/Frequentist Divide. J. Mach. Learn. Res. 11: 61-87 (2010) - [c16]Jakob Santner, Christian Leistner, Amir Saffari, Thomas Pock, Horst Bischof:
PROST: Parallel robust online simple tracking. CVPR 2010: 723-730 - [c15]Bernhard Zeisl, Christian Leistner, Amir Saffari, Horst Bischof:
On-line semi-supervised multiple-instance boosting. CVPR 2010: 1879 - [c14]Amir Saffari, Martin Godec, Thomas Pock, Christian Leistner, Horst Bischof:
Online multi-class LPBoost. CVPR 2010: 3570-3577 - [c13]Christian Leistner, Martin Godec, Amir Saffari, Horst Bischof:
On-Line Multi-view Forests for Tracking. DAGM-Symposium 2010: 493-502 - [c12]Christian Leistner, Amir Saffari, Horst Bischof:
MIForests: Multiple-Instance Learning with Randomized Trees. ECCV (6) 2010: 29-42 - [c11]Amir Saffari, Christian Leistner, Martin Godec, Horst Bischof:
Robust Multi-View Boosting with Priors. ECCV (3) 2010: 776-789 - [c10]Martin Godec, Christian Leistner, Amir Saffari, Horst Bischof:
On-Line Random Naive Bayes for Tracking. ICPR 2010: 3545-3548
2000 – 2009
- 2009
- [c9]Jakob Santner, Markus Unger, Thomas Pock, Christian Leistner, Amir Saffari, Horst Bischof:
Interactive Texture Segmentation using Random Forests and Total Variation. BMVC 2009: 1-12 - [c8]Amir Saffari, Christian Leistner, Horst Bischof:
Regularized multi-class semi-supervised boosting. CVPR 2009: 967-974 - [c7]Christian Leistner, Amir Saffari, Jakob Santner, Horst Bischof:
Semi-Supervised Random Forests. ICCV 2009: 506-513 - [c6]Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof:
On robustness of on-line boosting - a competitive study. ICCV Workshops 2009: 1362-1369 - [c5]Amir Saffari, Christian Leistner, Jakob Santner, Martin Godec, Horst Bischof:
On-line Random Forests. ICCV Workshops 2009: 1393-1400 - 2008
- [j2]Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley:
Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge. Neural Networks 21(2-3): 544-550 (2008) - [c4]Amir Saffari, Horst Bischof:
Boosting for Model-Based Data Clustering. DAGM-Symposium 2008: 51-60 - [c3]Amir Saffari, Helmut Grabner, Horst Bischof:
SERBoost: Semi-supervised Boosting with Expectation Regularization. ECCV (3) 2008: 588-601 - 2007
- [c2]Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley:
Agnostic Learning vs. Prior Knowledge Challenge. IJCNN 2007: 829-834 - 2006
- [j1]Amir Saffari:
Book Review: "complex Worlds from Simpler Nervous Systems", by Frederick R. Prete (Editor). Int. J. Comput. Intell. Appl. 6(4): 569-572 (2006) - [c1]Isabelle Guyon, Amir Reza Saffari Azar Alamdari, Gideon Dror, Joachim M. Buhmann:
PerformancePrediction Challenge. IJCNN 2006: 1649-1656 - [p1]Amir Reza Saffari Azar Alamdari:
Variable Selection using Correlation and Single Variable Classifier Methods: Applications. Feature Extraction 2006: 343-358
Coauthor Index
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last updated on 2024-04-24 22:59 CEST by the dblp team
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