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ORCIDMina Alibeigi
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2020 – today
- 2024
[j5]Ali Zoljodi
, Sadegh Abadijou, Mina Alibeigi, Masoud Daneshtalab:
Contrastive Learning for Lane Detection via cross-similarity. Pattern Recognit. Lett. 185: 175-183 (2024)- [c7]Hannes Eriksson, Tommy Tram, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. AAMAS 2024: 516-524 - [i10]Xinchi Qiu, Yan Gao, Lorenzo Sani, Heng Pan, Wanru Zhao, Pedro P. B. de Gusmao, Mina Alibeigi, Alex Iacob, Nicholas D. Lane:
FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients. CoRR abs/2402.10191 (2024) - 2023
- [j4]Hamid Mousavi, Mohammad Loni, Mina Alibeigi, Masoud Daneshtalab:
DASS: Differentiable Architecture Search for Sparse Neural Networks. ACM Trans. Embed. Comput. Syst. 22(5s): 105:1-105:21 (2023) - [c6]Yasar Abbas Ur Rehman, Yan Gao, Pedro Porto Buarque de Gusmão, Mina Alibeigi, Jiajun Shen, Nicholas D. Lane:
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning. ICCV 2023: 16418-16427 - [c5]Mina Alibeigi, William Ljungbergh, Adam Tonderski, Georg Hess, Adam Lilja, Carl Lindström, Daria Motorniuk, Junsheng Fu, Jenny Widahl, Christoffer Petersson:
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving. ICCV 2023: 20121-20131 - [c4]Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi:
FedVal: Different good or different bad in federated learning. USENIX Security Symposium 2023: 6365-6380 - [c3]Yadong Mao, Zhuqi Xiao, Che-Tsung Lin, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Christopher Zach, Mina Alibeigi:
Decentralized Training of 3D Lane Detection with Automatic Labeling Using HD Maps. VTC2023-Spring 2023: 1-7 - [i9]Hannes Eriksson, Debabrota Basu, Tommy Tram, Mina Alibeigi, Christos Dimitrakakis:
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. CoRR abs/2302.09273 (2023) - [i8]Mina Alibeigi, William Ljungbergh, Adam Tonderski, Georg Hess, Adam Lilja, Carl Lindström, Daria Motorniuk, Junsheng Fu, Jenny Widahl, Christoffer Petersson:
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving. CoRR abs/2305.02008 (2023) - [i7]Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi:
FedVal: Different good or different bad in federated learning. CoRR abs/2306.04040 (2023) - [i6]Yasar Abbas Ur Rehman, Yan Gao, Pedro Porto Buarque de Gusmão, Mina Alibeigi, Jiajun Shen, Nicholas D. Lane:
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning. CoRR abs/2307.07393 (2023) - [i5]Ali Zoljodi, Sadegh Abadijou, Mina Alibeigi, Masoud Daneshtalab:
Contrastive Learning for Lane Detection via Cross-Similarity. CoRR abs/2308.08242 (2023) - 2022
- [c2]Ali Zoljodi, Mohammad Loni, Sadegh Abadijou, Mina Alibeigi, Masoud Daneshtalab:
3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane Detection. ICANN (1) 2022: 404-415 - [c1]Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning. UAI 2022: 631-640 - [i4]Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty. CoRR abs/2203.10045 (2022) - [i3]Hamid Mousavi, Mohammad Loni, Mina Alibeigi, Masoud Daneshtalab:
PR-DARTS: Pruning-Based Differentiable Architecture Search. CoRR abs/2207.06968 (2022) - 2021
- [i2]Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning. CoRR abs/2102.11075 (2021)
2010 – 2019
- 2017
- [j3]Mina Alibeigi, Sadegh Rabiee, Majid Nili Ahmadabadi:
Inverse Kinematics Based Human Mimicking System using Skeletal Tracking Technology. J. Intell. Robotic Syst. 85(1): 27-45 (2017) - [j2]Mina Alibeigi, Majid Nili Ahmadabadi, Babak Nadjar Araabi:
A Fast, Robust, and Incremental Model for Learning High-Level Concepts From Human Motions by Imitation. IEEE Trans. Robotics 33(1): 153-168 (2017) - [i1]Mina Alibeigi, Majid Nili Ahmadabadi, Babak Nadjar Araabi:
Incremental learning of high-level concepts by imitation. CoRR abs/1704.04408 (2017) - 2012
- [j1]Mina Alibeigi, Sattar Hashemi, Ali Hamzeh:
DBFS: An effective Density Based Feature Selection scheme for small sample size and high dimensional imbalanced data sets. Data Knowl. Eng. 81-82: 67-103 (2012)
Coauthor Index
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