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Mohamad Ali Torkamani
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2020 – today
- 2024
- [c11]Zhichao Hou, Minhua Lin, MohamadAli Torkamani, Suhang Wang, Xiaorui Liu:
Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier. DSAA 2024: 1-2 - [c10]Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada:
Structural Fairness-aware Active Learning for Graph Neural Networks. ICLR 2024 - [i7]Zhichao Hou, Mina Ghashami, Mikhail Kuznetsov, MohamadAli Torkamani:
HLogformer: A Hierarchical Transformer for Representing Log Data. CoRR abs/2408.16803 (2024) - [i6]Zhichao Hou, MohamadAli Torkamani, Hamid Krim, Xiaorui Liu:
Robustness Reprogramming for Representation Learning. CoRR abs/2410.04577 (2024) - [i5]Kay Liu, Jiahao Ding, MohamadAli Torkamani, Philip S. Yu:
TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale. CoRR abs/2412.00984 (2024) - 2023
- [c9]Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang:
Alternately Optimized Graph Neural Networks. ICML 2023: 12411-12429 - [c8]Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu:
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation. ICML 2023: 38926-38937 - [c7]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. NeurIPS 2023 - [i4]Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu:
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation. CoRR abs/2302.01503 (2023) - [i3]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. CoRR abs/2305.15822 (2023) - 2020
- [c6]MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis:
Differential Equation Units: Learning Functional Forms of Activation Functions from Data. AAAI 2020: 6030-6037
2010 – 2019
- 2019
- [i2]MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas:
Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions. CoRR abs/1905.07685 (2019) - [i1]MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis:
Differential Equation Units: Learning Functional Forms of Activation Functions from Data. CoRR abs/1909.03069 (2019) - 2018
- [c5]Mohamad Ali Torkamani, Malhar Jhaveri, Jynelle Mellen, Michael Brown-Hayes, James Chung, Bei Pan, Hakan Kardes:
Engagement Scoring for Care-gap Intervention Optimization. HealthRecSys@RecSys 2018: 53-56 - [c4]Soheil Jamshidi, Mohamad Ali Torkamani, Jynelle Mellen, Malhar Jhaveri, Penny Pan, James Chung, Hakan Kardes:
A Hybrid Health Journey Recommender System Using Electronic Medical Records. HealthRecSys@RecSys 2018: 57-62 - 2014
- [c3]MohamadAli Torkamani, Daniel Lowd:
On Robustness and Regularization of Structural Support Vector Machines. ICML 2014: 577-585 - 2013
- [c2]MohamadAli Torkamani, Daniel Lowd:
Convex Adversarial Collective Classification. ICML (1) 2013: 642-650 - 2012
- [c1]MohamadAli Torkamani, Daniel Lowd:
Convex Adversarial Collective Classification. StarAI@UAI 2012
Coauthor Index
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